首页|Study Findings on Robotics Are Outlined in Reports from Beijing University of Te chnology (Multi-source Decision-making Information Fusion Framework for Evaluati ng Coexisting-cooperativecognitive Capabilities of Collaborative Robots Using T ext ...)
Study Findings on Robotics Are Outlined in Reports from Beijing University of Te chnology (Multi-source Decision-making Information Fusion Framework for Evaluati ng Coexisting-cooperativecognitive Capabilities of Collaborative Robots Using T ext ...)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news reporting originating from Beijing, People's Re public of China, by NewsRx correspondents, research stated, "To effectively addr ess the requirements of deeply coexisting-cooperative-cognitive (Tri-Co) interac tions among humans, robots, and the environment within the context of Industry 4 .0, it becomes crucial to conduct evaluation research on Tri-Co capabilities (TC Cs) of collaborative robots (cobots), which is a knowledgeintensive task. Howev er, existing research on performance evaluation of cobots has not yet establishe d a common method for constructing a complete performance evaluation index syste m." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). Our news editors obtained a quote from the research from the Beijing University of Technology, "The testing methods lack a design basis and fail to evaluate the performance of cobots through operational tasks in industrial production or dai ly life from the perspective of test tasks. Furthermore, these methods do not fa cilitate the fusion of multi-source subjective and objective decision-making inf ormation, which includes both the knowledge of experts and fundamental parameter s of cobots. To this end, this study proposes a multi-source decision-making inf ormation fusion framework for evaluating the TCCs of cobots. This framework incl udes a construction method for an evaluation index system that fuses subjective and objective elements based on statistics, text clustering, and closed-loop fee dback mechanism. It also incorporates TCCs test tasks, and an improved fuzzy ana lytic network process (IFANP). Additionally, it incorporates a combination weigh ting method that aims to minimise both subjective and objective weights deviatio ns. This framework effectively integrates the subjective knowledge of experts wi th the objective fundamental parameters of cobots. It accomplishes local TCCs ev aluation from the perspective of test tasks. Additionally, it achieves global TC Cs evaluation by combining basic performance evaluation indices and the performa nce of completing the test tasks. A case by Rethink Sawyer (Sawyer) is presented to demonstrate the application process and viability of the developed framework ."
BeijingPeople's Republic of ChinaAsi aEmerging TechnologiesMachine LearningNano-robotRoboticsBeijing Univer sity of Technology
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