research paper about robotics in the philippines

Diffusion of Robotics in the Philippines: Impact of Policies, Laws, R & D, and Word of Mouth

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Republic of the Philippines " Robotic Health and Impact Force Monitoring with Mobile Application " Thesis II The Problem and Its Background

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Schools in the Philippines are now implementing robotics subject in their K-12 Curriculum for the students to learn the concepts of programming robots, including St Mary's College Quezon City which started having robotics in SY 2016-2017. Thus, it will be significant to find out the students' perceptions on robotics as a tool for learning. The researchers will use phenomenology as their research design. The research includes purposively chosen informants who have varied experiences in robotics. Three (3) informants have competed in a robotics competition. Three (3) informants have taken the subject but have not competed in a robotics competition. One (1) informant is a teacher of the Robotics subject. A semi-structured interview guide was used to gather relevant data. The informants deem that they had acquired these 21st century skills: a) Critical Thinking; b) Collaboration; c) Creativity; d) Technology Literacy; e) Leadership; f) Social Skills; g) Communication; h) Productivity, through robotics classes. The informants also believe that robotics enhanced their 21st century skills because they are able to use the skills that they develop and acquire in robotics in their daily lives. Struggles include the limited slots in the robotics training program -only for students who excel and meet the standards of having a gold medal in robotics from the previous year. Thus, other students are not able to fully experience the beauty of robotics. The Robotics program was the school’s innovative program to make sure that students are at part with global standards. Based on their feedback, Robotics has helped them improve their 21st century skills and learned something they can apply in their daily lives. However, the school should also consider offering the program to interested students who would like to have the same opportunities as those who have higher skills in robotics.

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research paper about robotics in the philippines

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Industrial Robotics - Philippines

Philippines
Revenue in the Industrial Robotics market is projected to reach US$21.51m in 2024.
Other industry robotics dominates the market with a projected market volume of US$15.36m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2028) of 5.79%, resulting in a market volume of US$26.94m by 2028.
In global comparison, most revenue will be generated in China (US$1,440,000.00k in 2024).

Key regions: Germany , Italy , Australia , United Kingdom , France

Definition:

The Industrial Robotics market covers use cases that focus on the design, manufacturing, and deployment of robotic systems for industrial applications. The market encompasses the use of robots and automation technologies in manufacturing processes, assembly lines, and other industrial settings. This is to improve productivity, efficiency, and precision.

A robot is defined as a powered machine that is programmable on two or more axes and has some degree of autonomy; it moves within its environment to perform its programmed tasks.

The top five industries that use robotics are the automotive, chemical, metal, electronic, and food industries; however, other industries are also implementing various robotics use cases, but not on the same scale as these top five.

The Industrial Robotics market is further split into Automotive Industry Robotics, Chemical Industry Robotics, Electric/Electronic Industry Robotics, Food Industry Robotics, Metal Industry Robotics, and Other Industry Robotics.

Additional information:

The market comprises revenues, volume, and the average price per newly installed robot. It also includes the share of collaborative robots, as well as a list of the key players in the market and their consolidated revenues. The market displays both B2B and B2C revenues, and the revenue is based on the country’s demand for robots. It is shown in manufacturer prices. Software revenues are not included, as industrial robots are mostly used with specific software solutions that belong to the company that deploys them.

Key players in the market include ABB, Epson Robotics, Midea Group, and Yaskawa Electric Corporation.

For more information on the data displayed, use the info button right next to the box.

Automotive Industry Robotics
Chemical Industry Robotics
Electric/Electronic Industry Robotics
Food Industry Robotics
Metal Industry Robotics
Other Industry Robotics

out-of-scope

robots used in non-industrial environments
Commercial Service Robotics
Consumer Service Robotics
Analyst Opinion

The current industrial revolution is driven by several new technologies, with industrial robotics as one of its key elements.

The connection between robotics, big data, cloud computing, cybersecurity, the Internet of Things, and further technology innovations will shape today’s economies. This enables Industry 4.0 to capitalize on the interconnected nature of machines, processes, and products to streamline and automate them. Therefore, the combination of Industry 4.0 trends is boosting the demand for industrial robotics.

In 2020, 2021, and 2022, however, the growth of the Industrial Robotics segment slowed down because of disrupted supply chains and the semiconductor shortage, caused by the COVID-19 pandemic and the Russia-Ukraine war. A recovery of the growth rates of all industry segments to a positive level is expected only by 2023.

In terms of the current revenue distribution within the Industrial Robotics segment, the two largest subsegments, Automotive Industry Robotics and Electric/Electronic Industry Robotics, account for more than 50% of the segment. However, Other Industry Robotics is expected to become the second-largest subsegment by 2026 and the largest subsegment by 2027. This demonstrates the enormous potential for new use cases of automation in industries that are not yet using robots.

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Collaborative Robots
Autonomous mobile robots
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Published: 18 April 2024

Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

James Shaw 1 , 13 ,
Joseph Ali 2 , 3 ,
Caesar A. Atuire 4 , 5 ,
Phaik Yeong Cheah 6 ,
Armando Guio Español 7 ,
Judy Wawira Gichoya 8 ,
Adrienne Hunt 9 ,
Daudi Jjingo 10 ,
Katherine Littler 9 ,
Daniela Paolotti 11 &
Effy Vayena 12

BMC Medical Ethics volume 25 , Article number: 46 ( 2024 ) Cite this article

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The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

Conclusions

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

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Introduction

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice [ 1 , 2 , 3 ]. Beyond the growing number of AI applications being implemented in health care, capabilities of AI models such as Large Language Models (LLMs) expand the potential reach and significance of AI technologies across health-related fields [ 4 , 5 ]. Discussion about effective, ethical governance of AI technologies has spanned a range of governance approaches, including government regulation, organizational decision-making, professional self-regulation, and research ethics review [ 6 , 7 , 8 ]. In this paper, we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health research, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Although applications of AI for research, health care, and public health are diverse and advancing rapidly, the insights generated at the forum remain highly relevant from a global health perspective. After summarizing important context for work in this domain, we highlight categories of ethical issues emphasized at the forum for attention from a research ethics perspective internationally. We then outline strategies proposed for research, innovation, and governance to support more ethical AI for global health.

In this paper, we adopt the definition of AI systems provided by the Organization for Economic Cooperation and Development (OECD) as our starting point. Their definition states that an AI system is “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy” [ 9 ]. The conceptualization of an algorithm as helping to constitute an AI system, along with hardware, other elements of software, and a particular context of use, illustrates the wide variety of ways in which AI can be applied. We have found it useful to differentiate applications of AI in research as those classified as “AI systems for discovery” and “AI systems for intervention”. An AI system for discovery is one that is intended to generate new knowledge, for example in drug discovery or public health research in which researchers are seeking potential targets for intervention, innovation, or further research. An AI system for intervention is one that directly contributes to enacting an intervention in a particular context, for example informing decision-making at the point of care or assisting with accuracy in a surgical procedure.

The mandate of the GFBR is to take a broad view of what constitutes research and its regulation in global health, with special attention to bioethics in Low- and Middle- Income Countries. AI as a group of technologies demands such a broad view. AI development for health occurs in a variety of environments, including universities and academic health sciences centers where research ethics review remains an important element of the governance of science and innovation internationally [ 10 , 11 ]. In these settings, research ethics committees (RECs; also known by different names such as Institutional Review Boards or IRBs) make decisions about the ethical appropriateness of projects proposed by researchers and other institutional members, ultimately determining whether a given project is allowed to proceed on ethical grounds [ 12 ].

However, research involving AI for health also takes place in large corporations and smaller scale start-ups, which in some jurisdictions fall outside the scope of research ethics regulation. In the domain of AI, the question of what constitutes research also becomes blurred. For example, is the development of an algorithm itself considered a part of the research process? Or only when that algorithm is tested under the formal constraints of a systematic research methodology? In this paper we take an inclusive view, in which AI development is included in the definition of research activity and within scope for our inquiry, regardless of the setting in which it takes place. This broad perspective characterizes the approach to “research ethics” we take in this paper, extending beyond the work of RECs to include the ethical analysis of the wide range of activities that constitute research as the generation of new knowledge and intervention in the world.

Ethical governance of AI in global health

The ethical governance of AI for global health has been widely discussed in recent years. The World Health Organization (WHO) released its guidelines on ethics and governance of AI for health in 2021, endorsing a set of six ethical principles and exploring the relevance of those principles through a variety of use cases. The WHO guidelines also provided an overview of AI governance, defining governance as covering “a range of steering and rule-making functions of governments and other decision-makers, including international health agencies, for the achievement of national health policy objectives conducive to universal health coverage.” (p. 81) The report usefully provided a series of recommendations related to governance of seven domains pertaining to AI for health: data, benefit sharing, the private sector, the public sector, regulation, policy observatories/model legislation, and global governance. The report acknowledges that much work is yet to be done to advance international cooperation on AI governance, especially related to prioritizing voices from Low- and Middle-Income Countries (LMICs) in global dialogue.

One important point emphasized in the WHO report that reinforces the broader literature on global governance of AI is the distribution of responsibility across a wide range of actors in the AI ecosystem. This is especially important to highlight when focused on research for global health, which is specifically about work that transcends national borders. Alami et al. (2020) discussed the unique risks raised by AI research in global health, ranging from the unavailability of data in many LMICs required to train locally relevant AI models to the capacity of health systems to absorb new AI technologies that demand the use of resources from elsewhere in the system. These observations illustrate the need to identify the unique issues posed by AI research for global health specifically, and the strategies that can be employed by all those implicated in AI governance to promote ethically responsible use of AI in global health research.

RECs and the regulation of research involving AI

RECs represent an important element of the governance of AI for global health research, and thus warrant further commentary as background to our paper. Despite the importance of RECs, foundational questions have been raised about their capabilities to accurately understand and address ethical issues raised by studies involving AI. Rahimzadeh et al. (2023) outlined how RECs in the United States are under-prepared to align with recent federal policy requiring that RECs review data sharing and management plans with attention to the unique ethical issues raised in AI research for health [ 13 ]. Similar research in South Africa identified variability in understanding of existing regulations and ethical issues associated with health-related big data sharing and management among research ethics committee members [ 14 , 15 ]. The effort to address harms accruing to groups or communities as opposed to individuals whose data are included in AI research has also been identified as a unique challenge for RECs [ 16 , 17 ]. Doerr and Meeder (2022) suggested that current regulatory frameworks for research ethics might actually prevent RECs from adequately addressing such issues, as they are deemed out of scope of REC review [ 16 ]. Furthermore, research in the United Kingdom and Canada has suggested that researchers using AI methods for health tend to distinguish between ethical issues and social impact of their research, adopting an overly narrow view of what constitutes ethical issues in their work [ 18 ].

The challenges for RECs in adequately addressing ethical issues in AI research for health care and public health exceed a straightforward survey of ethical considerations. As Ferretti et al. (2021) contend, some capabilities of RECs adequately cover certain issues in AI-based health research, such as the common occurrence of conflicts of interest where researchers who accept funds from commercial technology providers are implicitly incentivized to produce results that align with commercial interests [ 12 ]. However, some features of REC review require reform to adequately meet ethical needs. Ferretti et al. outlined weaknesses of RECs that are longstanding and those that are novel to AI-related projects, proposing a series of directions for development that are regulatory, procedural, and complementary to REC functionality. The work required on a global scale to update the REC function in response to the demands of research involving AI is substantial.

These issues take greater urgency in the context of global health [ 19 ]. Teixeira da Silva (2022) described the global practice of “ethics dumping”, where researchers from high income countries bring ethically contentious practices to RECs in low-income countries as a strategy to gain approval and move projects forward [ 20 ]. Although not yet systematically documented in AI research for health, risk of ethics dumping in AI research is high. Evidence is already emerging of practices of “health data colonialism”, in which AI researchers and developers from large organizations in high-income countries acquire data to build algorithms in LMICs to avoid stricter regulations [ 21 ]. This specific practice is part of a larger collection of practices that characterize health data colonialism, involving the broader exploitation of data and the populations they represent primarily for commercial gain [ 21 , 22 ]. As an additional complication, AI algorithms trained on data from high-income contexts are unlikely to apply in straightforward ways to LMIC settings [ 21 , 23 ]. In the context of global health, there is widespread acknowledgement about the need to not only enhance the knowledge base of REC members about AI-based methods internationally, but to acknowledge the broader shifts required to encourage their capabilities to more fully address these and other ethical issues associated with AI research for health [ 8 ].

Although RECs are an important part of the story of the ethical governance of AI for global health research, they are not the only part. The responsibilities of supra-national entities such as the World Health Organization, national governments, organizational leaders, commercial AI technology providers, health care professionals, and other groups continue to be worked out internationally. In this context of ongoing work, examining issues that demand attention and strategies to address them remains an urgent and valuable task.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, REC members and other actors to engage with challenges and opportunities specifically related to research ethics. Each year the GFBR meeting includes a series of case studies and keynotes presented in plenary format to an audience of approximately 100 people who have applied and been competitively selected to attend, along with small-group breakout discussions to advance thinking on related issues. The specific topic of the forum changes each year, with past topics including ethical issues in research with people living with mental health conditions (2021), genome editing (2019), and biobanking/data sharing (2018). The forum is intended to remain grounded in the practical challenges of engaging in research ethics, with special interest in low resource settings from a global health perspective. A post-meeting fellowship scheme is open to all LMIC participants, providing a unique opportunity to apply for funding to further explore and address the ethical challenges that are identified during the meeting.

In 2022, the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations (both short and long form) reporting on specific initiatives related to research ethics and AI for health, and 16 governance presentations (both short and long form) reporting on actual approaches to governing AI in different country settings. A keynote presentation from Professor Effy Vayena addressed the topic of the broader context for AI ethics in a rapidly evolving field. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. The 2-day forum addressed a wide range of themes. The conference report provides a detailed overview of each of the specific topics addressed while a policy paper outlines the cross-cutting themes (both documents are available at the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ ). As opposed to providing a detailed summary in this paper, we aim to briefly highlight central issues raised, solutions proposed, and the challenges facing the research ethics community in the years to come.

In this way, our primary aim in this paper is to present a synthesis of the challenges and opportunities raised at the GFBR meeting and in the planning process, followed by our reflections as a group of authors on their significance for governance leaders in the coming years. We acknowledge that the views represented at the meeting and in our results are a partial representation of the universe of views on this topic; however, the GFBR leadership invested a great deal of resources in convening a deeply diverse and thoughtful group of researchers and practitioners working on themes of bioethics related to AI for global health including those based in LMICs. We contend that it remains rare to convene such a strong group for an extended time and believe that many of the challenges and opportunities raised demand attention for more ethical futures of AI for health. Nonetheless, our results are primarily descriptive and are thus not explicitly grounded in a normative argument. We make effort in the Discussion section to contextualize our results by describing their significance and connecting them to broader efforts to reform global health research and practice.

Uniquely important ethical issues for AI in global health research

Presentations and group dialogue over the course of the forum raised several issues for consideration, and here we describe four overarching themes for the ethical governance of AI in global health research. Brief descriptions of each issue can be found in Table 1 . Reports referred to throughout the paper are available at the GFBR website provided above.

The first overarching thematic issue relates to the appropriateness of building AI technologies in response to health-related challenges in the first place. Case study presentations referred to initiatives where AI technologies were highly appropriate, such as in ear shape biometric identification to more accurately link electronic health care records to individual patients in Zambia (Alinani Simukanga). Although important ethical issues were raised with respect to privacy, trust, and community engagement in this initiative, the AI-based solution was appropriately matched to the challenge of accurately linking electronic records to specific patient identities. In contrast, forum participants raised questions about the appropriateness of an initiative using AI to improve the quality of handwashing practices in an acute care hospital in India (Niyoshi Shah), which led to gaming the algorithm. Overall, participants acknowledged the dangers of techno-solutionism, in which AI researchers and developers treat AI technologies as the most obvious solutions to problems that in actuality demand much more complex strategies to address [ 24 ]. However, forum participants agreed that RECs in different contexts have differing degrees of power to raise issues of the appropriateness of an AI-based intervention.

The second overarching thematic issue related to whether and how AI-based systems transfer from one national health context to another. One central issue raised by a number of case study presentations related to the challenges of validating an algorithm with data collected in a local environment. For example, one case study presentation described a project that would involve the collection of personally identifiable data for sensitive group identities, such as tribe, clan, or religion, in the jurisdictions involved (South Africa, Nigeria, Tanzania, Uganda and the US; Gakii Masunga). Doing so would enable the team to ensure that those groups were adequately represented in the dataset to ensure the resulting algorithm was not biased against specific community groups when deployed in that context. However, some members of these communities might desire to be represented in the dataset, whereas others might not, illustrating the need to balance autonomy and inclusivity. It was also widely recognized that collecting these data is an immense challenge, particularly when historically oppressive practices have led to a low-trust environment for international organizations and the technologies they produce. It is important to note that in some countries such as South Africa and Rwanda, it is illegal to collect information such as race and tribal identities, re-emphasizing the importance for cultural awareness and avoiding “one size fits all” solutions.

The third overarching thematic issue is related to understanding accountabilities for both the impacts of AI technologies and governance decision-making regarding their use. Where global health research involving AI leads to longer-term harms that might fall outside the usual scope of issues considered by a REC, who is to be held accountable, and how? This question was raised as one that requires much further attention, with law being mixed internationally regarding the mechanisms available to hold researchers, innovators, and their institutions accountable over the longer term. However, it was recognized in breakout group discussion that many jurisdictions are developing strong data protection regimes related specifically to international collaboration for research involving health data. For example, Kenya’s Data Protection Act requires that any internationally funded projects have a local principal investigator who will hold accountability for how data are shared and used [ 25 ]. The issue of research partnerships with commercial entities was raised by many participants in the context of accountability, pointing toward the urgent need for clear principles related to strategies for engagement with commercial technology companies in global health research.

The fourth and final overarching thematic issue raised here is that of consent. The issue of consent was framed by the widely shared recognition that models of individual, explicit consent might not produce a supportive environment for AI innovation that relies on the secondary uses of health-related datasets to build AI algorithms. Given this recognition, approaches such as community oversight of health data uses were suggested as a potential solution. However, the details of implementing such community oversight mechanisms require much further attention, particularly given the unique perspectives on health data in different country settings in global health research. Furthermore, some uses of health data do continue to require consent. One case study of South Africa, Nigeria, Kenya, Ethiopia and Uganda suggested that when health data are shared across borders, individual consent remains necessary when data is transferred from certain countries (Nezerith Cengiz). Broader clarity is necessary to support the ethical governance of health data uses for AI in global health research.

Recommendations for ethical governance of AI in global health research

Dialogue at the forum led to a range of suggestions for promoting ethical conduct of AI research for global health, related to the various roles of actors involved in the governance of AI research broadly defined. The strategies are written for actors we refer to as “governance leaders”, those people distributed throughout the AI for global health research ecosystem who are responsible for ensuring the ethical and socially responsible conduct of global health research involving AI (including researchers themselves). These include RECs, government regulators, health care leaders, health professionals, corporate social accountability officers, and others. Enacting these strategies would bolster the ethical governance of AI for global health more generally, enabling multiple actors to fulfill their roles related to governing research and development activities carried out across multiple organizations, including universities, academic health sciences centers, start-ups, and technology corporations. Specific suggestions are summarized in Table 2 .

First, forum participants suggested that governance leaders including RECs, should remain up to date on recent advances in the regulation of AI for health. Regulation of AI for health advances rapidly and takes on different forms in jurisdictions around the world. RECs play an important role in governance, but only a partial role; it was deemed important for RECs to acknowledge how they fit within a broader governance ecosystem in order to more effectively address the issues within their scope. Not only RECs but organizational leaders responsible for procurement, researchers, and commercial actors should all commit to efforts to remain up to date about the relevant approaches to regulating AI for health care and public health in jurisdictions internationally. In this way, governance can more adequately remain up to date with advances in regulation.

Second, forum participants suggested that governance leaders should focus on ethical governance of health data as a basis for ethical global health AI research. Health data are considered the foundation of AI development, being used to train AI algorithms for various uses [ 26 ]. By focusing on ethical governance of health data generation, sharing, and use, multiple actors will help to build an ethical foundation for AI development among global health researchers.

Third, forum participants believed that governance processes should incorporate AI impact assessments where appropriate. An AI impact assessment is the process of evaluating the potential effects, both positive and negative, of implementing an AI algorithm on individuals, society, and various stakeholders, generally over time frames specified in advance of implementation [ 27 ]. Although not all types of AI research in global health would warrant an AI impact assessment, this is especially relevant for those studies aiming to implement an AI system for intervention into health care or public health. Organizations such as RECs can use AI impact assessments to boost understanding of potential harms at the outset of a research project, encouraging researchers to more deeply consider potential harms in the development of their study.

Fourth, forum participants suggested that governance decisions should incorporate the use of environmental impact assessments, or at least the incorporation of environment values when assessing the potential impact of an AI system. An environmental impact assessment involves evaluating and anticipating the potential environmental effects of a proposed project to inform ethical decision-making that supports sustainability [ 28 ]. Although a relatively new consideration in research ethics conversations [ 29 ], the environmental impact of building technologies is a crucial consideration for the public health commitment to environmental sustainability. Governance leaders can use environmental impact assessments to boost understanding of potential environmental harms linked to AI research projects in global health over both the shorter and longer terms.

Fifth, forum participants suggested that governance leaders should require stronger transparency in the development of AI algorithms in global health research. Transparency was considered essential in the design and development of AI algorithms for global health to ensure ethical and accountable decision-making throughout the process. Furthermore, whether and how researchers have considered the unique contexts into which such algorithms may be deployed can be surfaced through stronger transparency, for example in describing what primary considerations were made at the outset of the project and which stakeholders were consulted along the way. Sharing information about data provenance and methods used in AI development will also enhance the trustworthiness of the AI-based research process.

Sixth, forum participants suggested that governance leaders can encourage or require community engagement at various points throughout an AI project. It was considered that engaging patients and communities is crucial in AI algorithm development to ensure that the technology aligns with community needs and values. However, participants acknowledged that this is not a straightforward process. Effective community engagement requires lengthy commitments to meeting with and hearing from diverse communities in a given setting, and demands a particular set of skills in communication and dialogue that are not possessed by all researchers. Encouraging AI researchers to begin this process early and build long-term partnerships with community members is a promising strategy to deepen community engagement in AI research for global health. One notable recommendation was that research funders have an opportunity to incentivize and enable community engagement with funds dedicated to these activities in AI research in global health.

Seventh, forum participants suggested that governance leaders can encourage researchers to build strong, fair partnerships between institutions and individuals across country settings. In a context of longstanding imbalances in geopolitical and economic power, fair partnerships in global health demand a priori commitments to share benefits related to advances in medical technologies, knowledge, and financial gains. Although enforcement of this point might be beyond the remit of RECs, commentary will encourage researchers to consider stronger, fairer partnerships in global health in the longer term.

Eighth, it became evident that it is necessary to explore new forms of regulatory experimentation given the complexity of regulating a technology of this nature. In addition, the health sector has a series of particularities that make it especially complicated to generate rules that have not been previously tested. Several participants highlighted the desire to promote spaces for experimentation such as regulatory sandboxes or innovation hubs in health. These spaces can have several benefits for addressing issues surrounding the regulation of AI in the health sector, such as: (i) increasing the capacities and knowledge of health authorities about this technology; (ii) identifying the major problems surrounding AI regulation in the health sector; (iii) establishing possibilities for exchange and learning with other authorities; (iv) promoting innovation and entrepreneurship in AI in health; and (vi) identifying the need to regulate AI in this sector and update other existing regulations.

Ninth and finally, forum participants believed that the capabilities of governance leaders need to evolve to better incorporate expertise related to AI in ways that make sense within a given jurisdiction. With respect to RECs, for example, it might not make sense for every REC to recruit a member with expertise in AI methods. Rather, it will make more sense in some jurisdictions to consult with members of the scientific community with expertise in AI when research protocols are submitted that demand such expertise. Furthermore, RECs and other approaches to research governance in jurisdictions around the world will need to evolve in order to adopt the suggestions outlined above, developing processes that apply specifically to the ethical governance of research using AI methods in global health.

Research involving the development and implementation of AI technologies continues to grow in global health, posing important challenges for ethical governance of AI in global health research around the world. In this paper we have summarized insights from the 2022 GFBR, focused specifically on issues in research ethics related to AI for global health research. We summarized four thematic challenges for governance related to AI in global health research and nine suggestions arising from presentations and dialogue at the forum. In this brief discussion section, we present an overarching observation about power imbalances that frames efforts to evolve the role of governance in global health research, and then outline two important opportunity areas as the field develops to meet the challenges of AI in global health research.

Dialogue about power is not unfamiliar in global health, especially given recent contributions exploring what it would mean to de-colonize global health research, funding, and practice [ 30 , 31 ]. Discussions of research ethics applied to AI research in global health contexts are deeply infused with power imbalances. The existing context of global health is one in which high-income countries primarily located in the “Global North” charitably invest in projects taking place primarily in the “Global South” while recouping knowledge, financial, and reputational benefits [ 32 ]. With respect to AI development in particular, recent examples of digital colonialism frame dialogue about global partnerships, raising attention to the role of large commercial entities and global financial capitalism in global health research [ 21 , 22 ]. Furthermore, the power of governance organizations such as RECs to intervene in the process of AI research in global health varies widely around the world, depending on the authorities assigned to them by domestic research governance policies. These observations frame the challenges outlined in our paper, highlighting the difficulties associated with making meaningful change in this field.

Despite these overarching challenges of the global health research context, there are clear strategies for progress in this domain. Firstly, AI innovation is rapidly evolving, which means approaches to the governance of AI for health are rapidly evolving too. Such rapid evolution presents an important opportunity for governance leaders to clarify their vision and influence over AI innovation in global health research, boosting the expertise, structure, and functionality required to meet the demands of research involving AI. Secondly, the research ethics community has strong international ties, linked to a global scholarly community that is committed to sharing insights and best practices around the world. This global community can be leveraged to coordinate efforts to produce advances in the capabilities and authorities of governance leaders to meaningfully govern AI research for global health given the challenges summarized in our paper.

Limitations

Our paper includes two specific limitations that we address explicitly here. First, it is still early in the lifetime of the development of applications of AI for use in global health, and as such, the global community has had limited opportunity to learn from experience. For example, there were many fewer case studies, which detail experiences with the actual implementation of an AI technology, submitted to GFBR 2022 for consideration than was expected. In contrast, there were many more governance reports submitted, which detail the processes and outputs of governance processes that anticipate the development and dissemination of AI technologies. This observation represents both a success and a challenge. It is a success that so many groups are engaging in anticipatory governance of AI technologies, exploring evidence of their likely impacts and governing technologies in novel and well-designed ways. It is a challenge that there is little experience to build upon of the successful implementation of AI technologies in ways that have limited harms while promoting innovation. Further experience with AI technologies in global health will contribute to revising and enhancing the challenges and recommendations we have outlined in our paper.

Second, global trends in the politics and economics of AI technologies are evolving rapidly. Although some nations are advancing detailed policy approaches to regulating AI more generally, including for uses in health care and public health, the impacts of corporate investments in AI and political responses related to governance remain to be seen. The excitement around large language models (LLMs) and large multimodal models (LMMs) has drawn deeper attention to the challenges of regulating AI in any general sense, opening dialogue about health sector-specific regulations. The direction of this global dialogue, strongly linked to high-profile corporate actors and multi-national governance institutions, will strongly influence the development of boundaries around what is possible for the ethical governance of AI for global health. We have written this paper at a point when these developments are proceeding rapidly, and as such, we acknowledge that our recommendations will need updating as the broader field evolves.

Ultimately, coordination and collaboration between many stakeholders in the research ethics ecosystem will be necessary to strengthen the ethical governance of AI in global health research. The 2022 GFBR illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Data availability

All data and materials analyzed to produce this paper are available on the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ .

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Acknowledgements

We would like to acknowledge the outstanding contributions of the attendees of GFBR 2022 in Cape Town, South Africa. This paper is authored by members of the GFBR 2022 Planning Committee. We would like to acknowledge additional members Tamra Lysaght, National University of Singapore, and Niresh Bhagwandin, South African Medical Research Council, for their input during the planning stages and as reviewers of the applications to attend the Forum.

This work was supported by Wellcome [222525/Z/21/Z], the US National Institutes of Health, the UK Medical Research Council (part of UK Research and Innovation), and the South African Medical Research Council through funding to the Global Forum on Bioethics in Research.

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JS led the writing, contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. CA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. PYC contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AE contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JWG contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AH contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DJ contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. KL contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DP contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. EV contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper.

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Shaw, J., Ali, J., Atuire, C.A. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 25 , 46 (2024). https://doi.org/10.1186/s12910-024-01044-w

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ABHIKAHA: Aerial Collision Avoidance in Quadcopter using Cloud Robotics
The Evolution Of Cloud Robotics: A Survey
Sliding Autonomy in Cloud Robotics Services for Smart City Applications
CORE: A Cloud-based Object Recognition Engine for Robotics
A Software Product Line Approach for Configuring Cloud Robotics Applications
Cloud robotics and automation: A survey of related work
ROCHAS: Robotics and Cloud-assisted Healthcare System for Empty Nester

Swarm Robotics

Evolution of Task Partitioning in Swarm Robotics
GESwarm: Grammatical Evolution for the Automatic Synthesis of Collective Behaviors in Swarm Robotics
A Concise Chronological Reassess Of Different Swarm Intelligence Methods With Multi Robotics Approach
The Swarm/Potential Model: Modeling Robotics Swarms with Measure-valued Recursions Associated to Random Finite Sets
The TAM: ABSTRACTing complex tasks in swarm robotics research
Task Allocation in Foraging Robot Swarms: The Role of Information Sharing
Robotics on the Battlefield Part II
Implementation Of Load Sharing Using Swarm Robotics
An Investigation of Environmental Influence on the Benefits of Adaptation Mechanisms in Evolutionary Swarm Robotics

Soft Robotics

Soft Robotics: The Next Generation of Intelligent Machines
Soft Robotics: Transferring Theory to Application,” Soft Components for Soft Robots”
Advances in Soft Computing, Intelligent Robotics and Control
The BRICS Component Model: A Model-Based Development Paradigm For ComplexRobotics Software Systems
Soft Mechatronics for Human-Friendly Robotics
Seminar Soft-Robotics
Special Issue on Open Source Software-Supported Robotics Research.
Soft Brain-Machine Interfaces for Assistive Robotics: A Novel Control Approach
Towards A Robot Hardware ABSTRACT ion Layer (R-HAL) Leveraging the XBot Software Framework

Service Robotics

Fundamental Theories and Practice in Service Robotics
Natural Language Processing in Domestic Service Robotics
Localization and Mapping for Service Robotics Applications
Designing of Service Robot for Home Automation-Implementation
Benchmarking Speech Understanding in Service Robotics
The Cognitive Service Robotics Apartment
Planning with Task-oriented Knowledge Acquisition for A Service Robot
Cognitive Robotics
Meta-Morphogenesis theory as background to Cognitive Robotics and Developmental Cognitive Science
Experience-based Learning for Bayesian Cognitive Robotics
Weakly supervised strategies for natural object recognition in robotics
Robotics-Derived Requirements for the Internet of Things in the 5G Context
A Comparison of Modern Synthetic Character Design and Cognitive Robotics Architecture with the Human Nervous System
PREGO: An Action Language for Belief-Based Cognitive Robotics in Continuous Domains
The Role of Intention in Cognitive Robotics
On Cognitive Learning Methodologies for Cognitive Robotics
Relational Enhancement: A Framework for Evaluating and Designing Human-RobotRelationships
A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering
Spatial Cognition in Robotics
IOT Based Gesture Movement Recognize Robot
Deliberative Systems for Autonomous Robotics: A Brief Comparison Between Action-oriented and Timelines-based Approaches
Formal Modeling and Verification of Dynamic Reconfiguration of Autonomous RoboticsSystems
Robotics on its feet: Autonomous Climbing Robots
Implementation of Autonomous Metal Detection Robot with Image and Message Transmission using Cell Phone
Toward autonomous architecture: The convergence of digital design, robotics, and the built environment
Advances in Robotics Automation
Data-centered Dependencies and Opportunities for Robotics Process Automation in Banking
On the Combination of Gamification and Crowd Computation in Industrial Automation and Robotics Applications
Advances in RoboticsAutomation
Meshworm With Segment-Bending Anchoring for Colonoscopy. IEEE ROBOTICS AND AUTOMATION LETTERS. 2 (3) pp: 1718-1724.
Recent Advances in Robotics and Automation
Key Elements Towards Automation and Robotics in Industrialised Building System (IBS)
Knowledge Building, Innovation Networks, and Robotics in Math Education
The potential of a robotics summer course On Engineering Education
Robotics as an Educational Tool: Impact of Lego Mindstorms
Effective Planning Strategy in Robotics Education: An Embodied Approach
An innovative approach to School-Work turnover programme with Educational Robotics
The importance of educational robotics as a precursor of Computational Thinking in early childhood education
Pedagogical Robotics A way to Experiment and Innovate in Educational Teaching in Morocco
Learning by Making and Early School Leaving: an Experience with Educational Robotics
Robotics and Coding: Fostering Student Engagement
Computational Thinking with Educational Robotics
New Trends In Education Of Robotics
Educational robotics as an instrument of formation: a public elementary school case study
Developmental Situation and Strategy for Engineering Robot Education in China University
Towards the Humanoid Robot Butler
YAGI-An Easy and Light-Weighted Action-Programming Language for Education and Research in Artificial Intelligence and Robotics
Simultaneous Tracking and Reconstruction (STAR) of Objects and its Application in Educational Robotics Laboratories
The importance and purpose of simulation in robotics
An Educational Tool to Support Introductory Robotics Courses
Lollybot: Where Candy, Gaming, and Educational Robotics Collide
Assessing the Impact of an Autonomous Robotics Competition for STEM Education
Educational robotics for promoting 21st century skills
New Era for Educational Robotics: Replacing Teachers with a Robotic System to Teach Alphabet Writing
Robotics as a Learning Tool for Educational Transformation
The Herd of Educational Robotic Devices (HERD): Promoting Cooperation in RoboticsEducation
Robotics in physics education: fostering graphing abilities in kinematics
Enabling Rapid Prototyping in K-12 Engineering Education with BotSpeak, a UniversalRobotics Programming Language
Innovating in robotics education with Gazebo simulator and JdeRobot framework
How to Support Students’ Computational Thinking Skills in Educational Robotics Activities
Educational Robotics At Lower Secondary School
Evaluating the impact of robotics in education on pupils’ skills and attitudes
Imagining, Playing, and Coding with KIBO: Using Robotics to Foster Computational Thinking in Young Children
How Does a First LEGO League Robotics Program Provide Opportunities for Teaching Children 21st Century Skills
A Software-Based Robotic Vision Simulator For Use In Teaching Introductory Robotics Courses
Robotics Practical
A project-based strategy for teaching robotics using NI’s embedded-FPGA platform
Teaching a Core CS Concept through Robotics
Ms. Robot Will Be Teaching You: Robot Lecturers in Four Modes of Automated Remote Instruction
Robotic Competitions: Teaching Robotics and Real-Time Programming with LEGO Mindstorms
Visegrad Robotics Workshop-different ideas to teach and popularize robotics
LEGO® Mindstorms® EV3 Robotics Instructor Guide
DRAFT: for Automaatiop iv t22 MOKASIT: Multi Camera System for Robotics Monitoring and Teaching
MOKASIT: Multi Camera System for Robotics Monitoring and Teaching
Autonomous Robot Design and Build: Novel Hands-on Experience for Undergraduate Students
Semi-Autonomous Inspection Robot
Sumo Robot Competition
Engagement of students with Robotics-Competitions-like projects in a PBL Bsc Engineering course
Robo Camp K12 Inclusive Outreach Program: A three-step model of Effective Introducing Middle School Students to Computer Programming and Robotics
The Effectiveness of Robotics Competitions on Students’ Learning of Computer Science
Engaging with Mathematics: How mathematical art, robotics and other activities are used to engage students with university mathematics and promote
Design Elements of a Mobile Robotics Course Based on Student Feedback
Sixth-Grade Students’ Motivation and Development of Proportional Reasoning Skills While Completing Robotics Challenges
Student Learning of Computational Thinking in A Robotics Curriculum: Transferrable Skills and Relevant Factors
A Robotics-Focused Instructional Framework for Design-Based Research in Middle School Classrooms
Transforming a Middle and High School Robotics Curriculum
Geometric Algebra for Applications in Cybernetics: Image Processing, Neural Networks, Robotics and Integral Transforms
Experimenting and validating didactical activities in the third year of primary school enhanced by robotics technology

Construction

Bibliometric analysis on the status quo of robotics in construction
AtomMap: A Probabilistic Amorphous 3D Map Representation for Robotics and Surface Reconstruction
Robotic Design and Construction Culture: Ethnography in Osaka University’s Miyazaki Robotics Lab
Infrastructure Robotics: A Technology Enabler for Lunar In-Situ Resource Utilization, Habitat Construction and Maintenance
A Planar Robot Design And Construction With Maple
Robotics and Automations in Construction: Advanced Construction and FutureTechnology
Why robotics in mining
Examining Influences on the Evolution of Design Ideas in a First-Year Robotics Project
Mining Robotics
TIRAMISU: Technical survey, close-in-detection and disposal mine actions in Humanitarian Demining: challenges for Robotics Systems
Robotics for Sustainable Agriculture in Aquaponics
Design and Fabrication of Crop Analysis Agriculture Robot
Enhance Multi-Disciplinary Experience for Agriculture and Engineering Students with Agriculture Robotics Project
Work in progress: Robotics mapping of landmine and UXO contaminated areas
Robot Based Wireless Monitoring and Safety System for Underground Coal Mines using Zigbee Protocol: A Review
Minesweepers uses robotics’ awesomeness to raise awareness about landminesexplosive remnants of war
Intelligent Autonomous Farming Robot with Plant Disease Detection using Image Processing
Auotomatic Pick And Place Robot
Video Prompting to Teach Robotics and Coding to Students with Autism Spectrum Disorder
Bilateral Anesthesia Mumps After RobotAssisted Hysterectomy Under General Anesthesia: Two Case Reports
Future Prospects of Artificial Intelligence in Robotics Software, A healthcare Perspective
Designing new mechanism in surgical robotics
Open-Source Research Platforms and System Integration in Modern Surgical Robotics
Soft Tissue Robotics–The Next Generation
CORVUS Full-Body Surgical Robotics Research Platform
OP: Sense, a rapid prototyping research platform for surgical robotics
Preoperative Planning Simulator with Haptic Feedback for Raven-II Surgical Robotics Platform
Origins of Surgical Robotics: From Space to the Operating Room
Accelerometer Based Wireless Gesture Controlled Robot for Medical Assistance using Arduino Lilypad
The preliminary results of a force feedback control for Sensorized Medical Robotics
Medical robotics Regulatory, ethical, and legal considerations for increasing levels of autonomy
Robotics in General Surgery
Evolution Of Minimally Invasive Surgery: Conventional Laparoscopy Torobotics
Robust trocar detection and localization during robot-assisted endoscopic surgery
How can we improve the Training of Laparoscopic Surgery thanks to the Knowledge in Robotics
Discussion on robot-assisted laparoscopic cystectomy and Ileal neobladder surgery preoperative care
Robotics in Neurosurgery: Evolution, Current Challenges, and Compromises
Hybrid Rendering Architecture for Realtime and Photorealistic Simulation of Robot-Assisted Surgery
Robotics, Image Guidance, and Computer-Assisted Surgery in Otology/Neurotology
Neuro-robotics model of visual delusions
Neuro-Robotics
Robotics in the Rehabilitation of Neurological Conditions
What if a Robot Could Help Me Care for My Parents
A Robot to Provide Support in Stigmatizing Patient-Caregiver Relationships
A New Skeleton Model and the Motion Rhythm Analysis for Human Shoulder Complex Oriented to Rehabilitation Robotics
Towards Rehabilitation Robotics: Off-The-Shelf BCI Control of Anthropomorphic Robotic Arms
Rehabilitation Robotics 2013
Combined Estimation of Friction and Patient Activity in Rehabilitation Robotics
Brain, Mind and Body: Motion Behaviour Planning, Learning and Control in view of Rehabilitation and Robotics
Reliable Robotics – Diagnostics
Robotics for Successful Ageing
Upper Extremity Robotics Exoskeleton: Application, Structure And Actuation

Defence and Military

Voice Guided Military Robot for Defence Application
Design and Control of Defense Robot Based On Virtual Reality
AI, Robotics and Cyber: How Much will They Change Warfare
BORDER SECURITY ROBOT
Brain Controlled Robot for Indian Armed Force
Autonomous Military Robotics
Wireless Restrained Military Discoursed Robot
Bomb Detection And Defusion In Planes By Application Of Robotics
Impacts Of The Robotics Age On Naval Force Design, Effectiveness, And Acquisition

Space Robotics

Lego robotics teacher professional learning
New Planar Air-bearing Microgravity Simulator for Verification of Space Robotics Numerical Simulations and Control Algorithms
The Artemis Rover as an Example for Model Based Engineering in Space Robotics
Rearrangement planning using object-centric and robot-centric action spaces
Model-based Apprenticeship Learning for Robotics in High-dimensional Spaces
Emergent Roles, Collaboration and Computational Thinking in the Multi-Dimensional Problem Space of Robotics
Reaction Null Space of a multibody system with applications in robotics

Other Industries

Robotics in clothes manufacture
Recent Trends in Robotics and Computer Integrated Manufacturing: An Overview
Application Of Robotics In Dairy And Food Industries: A Review
Architecture for theatre robotics
Human-multi-robot team collaboration for efficent warehouse operation
A Robot-based Application for Physical Exercise Training
Application Of Robotics In Oil And Gas Refineries
Implementation of Robotics in Transmission Line Monitoring
Intelligent Wireless Fire Extinguishing Robot
Monitoring and Controlling of Fire Fighthing Robot using IOT
Robotics An Emerging Technology in Dairy Industry
Robotics and Law: A Survey
Increasing ECE Student Excitement through an International Marine Robotics Competition
Application of Swarm Robotics Systems to Marine Environmental Monitoring

Future of Robotics / Trends

The future of Robotics Technology
RoboticsAutomation Are Killing Jobs A Roadmap for the Future is Needed
The next big thing (s) in robotics
Robotics in Indian Industry-Future Trends
The Future of Robot Rescue Simulation Workshop
PreprintQuantum Robotics: Primer on Current Science and Future Perspectives
Emergent Trends in Robotics and Intelligent Systems

Robotics? Smarter in the Philippines!

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This is AI generated summarization, which may have errors. For context, always refer to the full article.

MANILA, Philippines – Sixteen-year-old Claire Reñosa had a lot to say.

Her sentences were peppered with the phrase “at the same time.” She rarely looked at the cameras, but constantly gazed over the shoulders of the audience packed in a small restaurant in Makati.

She has been a participant of the Philippine Robotics Olympiad (PRO) for the last three years, and was the Junior High School Open Category champion with her two other teammates during last year’s World Robot Olympiad in Malaysia.

Their gold medal-winning robot HERO (or Humanoid for Educational Reinforcement Operation) was inspired by the 2009 CNN Hero of the Year, Efren Peñaflorida, and his Kariton Revolution.

At the launch of the 12 th year of PRO last Friday, June 21, she had a lot to say about her experiences with the competition—from the skills and character she developed, down to the simpler joys like flying out to different countries to compete with other high school students.

She seemed too eager as she spoke, maybe due to her excitement for the new participants.

“So to those new participants in this competition, I hope you cherish this chance because not everyone has this [chance]. I hope [all] of us [enjoy] robotics.”

The Philippine Robotics Olympiad

Like Claire, more and more Filipino students are gaining interest with robotics, and the PRO i s an annual competition which aims to offer an opportunity for students to explore robots and robotic systems in schools. Every year, grand winners of the PRO represent the country in the World Robot Olympiad.

PRO national organizer Mylene Abiva said they expect over 400 public and private schools nationwide to participate in this year’s national competition. In her estimate, 40% of this number will come from public schools, while the majority or 60% will come from private schools.

“The public schools are now going head-to-head with the private schools. Before, they would feel quite intimidated with the private schools, but now, I believe that with the support of the Department of Education (DepEd), they [can now] focus [more] on the robotics program,” she said.

The PRO’s partnership with the Department of Science and Technology-Science Education Institute (DOST-SEI) started in 2004.

“I felt that the government has more reach with regards to the public schools, which I also want to get involved with,” Abiva said about the partnership.

Together with the DOST-SEI, they will launch a new robotics interschool competition this year called First Lego League Philippines, where students will conduct robot research and present their findings through a robot game.

In the previous years, the PRO has been open to elementary and high school students ages 10 to 16 years old. With the K to 12 law adding two more years to the basic education in the country, Abiva said they are looking to open it for 17- and 18-year-olds.

Robotics in the classroom

Along with the PRO, Abiva also launched the Philippine Robotics Academy (PRA) through the non-profit organization FELTA Multi-Media Inc.

The PRA is an integrated robotics curriculum provided to schools, as well as textbooks, kits, and computers to engage students in robotics education.

“It’s a school within a school. We help them, we provide them with the curriculum, and it’s an option of the school whether to integrate it with computer classes or Physics class or general science classes for [the] elementary level,” she said.

So far, only four schools in the country integrated the Academy in their curriculum: Claret School of Quezon City, Dr. Yanga’s College Inc., MCA Montessori School-Taguig, and St. Michael’s College of Biñan.

Dr. Lourdes Almeda Sese, president of St. Michael’s College of Biñan, take pride with the school as the first Robotics Academy in Laguna.

On their first year of implementation, they dedicated one hour of the weekly, 3-hour Computer class for the robotics curriculum. It was only implemented in the last two quarters of the school year, but the grades 4-7 students were quick learners.

“Starting from almost [no] knowledge, they have been able to move blocks for the first year of implementation, and that is only after…two quarters,” Robotics Club adviser Karla Maranan shared.

The teachers also observed a change of learning behavior among the students. “We really saw the change of behavior… before, they just get to be passive [in] class, but now they try to move and work and compute,” Basic Education Director Elena Manalo said.

The PRA is only being offered to private schools for now, although Abiva said they presented a grade 7 robotics curriculum to DepEd. It is an experimental program for the Science-oriented high schools nationwide.

“It started last year, but we are not sure how many schools have implemented,” she said.

‘Robotics is the future’

DOST Undersecretary Fortunato De La Pena said robotics is one of the platforms the country can depend on.

“Local technology works, so we will try to apply that to our local condition and we are aiming at what our secretary says a Smarter Philippines,” he added.

Last 2012, the DOST launched the Smarter Philippines campaign , a program that will use Information and Communication Technology (ICT) as “an enabling tool to provide more efficient and reliable services in some priority industries in the country”.

DOST-SEI Director Filma Brawner said programs like the PRO attract more students to take up science and technology (S&T) courses, which will hopefully lead to S&T careers. These programs aid schools where teaching science remains to be a challenge to educators.

“You can use robotics of course in areas like manufacturing, health areas, and so on. In terms of agriculture, you can also use robotics,” she added.

Abiva, on the other hand, wants both parents and students to see that there are jobs in the country when you go into any of the S&T careers.

“These students are the critical thinkers that the country needs for us to be a developed a country. We have so little scientists here in the Philippines. This is just a stepping stone that we are taking. It’s not a solve-all pill that we’re giving, but at least it’s a step for us to have hope for our country,” she said.

In Abiva’s Philippines, robotics is the future. It will be a country where robots do the menial jobs, while Filipinos do the real thinking, interacting, socializing, and researching. It will be a country where both can co-exist.

But for her, that kind of tomorrow will only happen when smart thinking starts today. – Rappler.com

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Title: research on robot path planning based on reinforcement learning.

Abstract: This project has conducted research on robot path planning based on Visual SLAM. The main work of this project is as follows: (1) Construction of Visual SLAM system. Research has been conducted on the basic architecture of Visual SLAM. A Visual SLAM system is developed based on ORB-SLAM3 system, which can conduct dense point cloud mapping. (2) The map suitable for two-dimensional path planning is obtained through map conversion. This part converts the dense point cloud map obtained by Visual SLAM system into an octomap and then performs projection transformation to the grid map. The map conversion converts the dense point cloud map containing a large amount of redundant map information into an extremely lightweight grid map suitable for path planning. (3) Research on path planning algorithm based on reinforcement learning. This project has conducted experimental comparisons between the Q-learning algorithm, the DQN algorithm, and the SARSA algorithm, and found that DQN is the algorithm with the fastest convergence and best performance in high-dimensional complex environments. This project has conducted experimental verification of the Visual SLAM system in a simulation environment. The experimental results obtained based on open-source dataset and self-made dataset prove the feasibility and effectiveness of the designed Visual SLAM system. At the same time, this project has also conducted comparative experiments on the three reinforcement learning algorithms under the same experimental condition to obtain the optimal algorithm under the experimental condition.

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Economic security in the Philippines: invitation for expressions of interest

Express your interest by 13 May 2024 to carry out a rapid evidence assessment of research literature on the economic resilience of the Philippines.

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Diffusion of Robotics in the Philippines: Impact of Policies, Laws, R
Robotics is one of the key emerging technologies laid in Industry 4.0. Currently, the Philippines is lagging with technological advancement compared to other ASEAN countries. Consequently, the areas with contributing factors in robotics' innovation advancement were revisited. The existing policies, laws, research publications, and public interest trends relating to robotics were used as input ...
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DOI: 10.1109/hnicem51456.2020.9400141 Corpus ID: 233332481; The Robotics and the Role on Agricultural Industry in the Philippines @article{Rogelio2020TheRA, title={The Robotics and the Role on Agricultural Industry in the Philippines}, author={Jayson P. Rogelio and Alvin B. Culaba and Elmer P. Dadios and Ryan Ray P. Vicerra and Argel A. Bandala}, journal={2020 IEEE 12th International ...
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Schools in the Philippines are now implementing robotics subject in their K-12 Curriculum for the students to learn the concepts of programming robots, including St Mary's College Quezon City which started having robotics in SY 2016-2017. Thus, it will be significant to find out the students' perceptions on robotics as a tool for learning. The researchers will use phenomenology as their ...
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The Robotics market in the Philippines is projected to grow by 0.16% (2024-2028) resulting in a market volume of US$60.95m in 2028. ... Get quick analyses with our professional research service
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SHS STEM-Robotics Research Project entitled "MANG-KALAKAL: A PROTOTYPE PROMOTING WASTE MANAGEMENT AND SEGREGATION IN LOCAL GOVERNMENT UNIT" was presented during the De La Salle University's Research Congress 2022. The said event with the theme: "Lessons from the Pandemic: Reinventing the Next Normal" was held last July 6-8, 2022 via Zoom. The paper was authored by […]
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