首页|New Findings on Robotics from Beijing Institute of Technology Summarized (Multi-agent Policy Learning-based Path Planning for Autonomous Mobile Robots)
New Findings on Robotics from Beijing Institute of Technology Summarized (Multi-agent Policy Learning-based Path Planning for Autonomous Mobile Robots)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Robotics are discussed in a new report. According to news reporting out of Beijing, People's Republic of China, by NewsRx editors, research stated, "The study addresses path planning problems for autonomous mobile robots (AMRs), considering their kinematics, where performance and responsiveness are often incompatible. This study proposes a multi-agent policy learning-based method to tackle this challenge in dynamic environments." Financial supporters for this research include National Key R&D Program of China, National Natural Science Foundation of China (NSFC), Beijing Institute of Technology (BIT) Research and Innovation Promoting Project. Our news journalists obtained a quote from the research from the Beijing Institute of Technology, "The proposed method features a centralized learning and decentralized execution-based path planning framework designed to meet performance and responsiveness requirements. The problem is modeled as a partial observation Markov Decision Process for policy learning while considering the kinematics using conventional neural networks. Then, an improved proximal policy optimization algorithm is developed with highlight experience replay that corrects failed experiences to speed up the learning processes. The experimental results show that the proposed method out-performs the baselines in both static and dynamic environments. The proposed method shortens the movement distance and time in static environments by about 29.1% and 5.7%, as well as in dynamic environments by about 21.1% and 20.4%, respectively."
BeijingPeople's Republic of ChinaAsiaEmerging TechnologiesMachine LearningNano-robotRoboticsBeijing Institute of Technology
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