首页|Research Findings from Shanghai Ocean University Update Understanding of Robotic s (Robotic Manipulator in Dynamic Environment with SAC Combing Attention Mechani sm and LSTM)
Research Findings from Shanghai Ocean University Update Understanding of Robotic s (Robotic Manipulator in Dynamic Environment with SAC Combing Attention Mechani sm and LSTM)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in robotics. Accordin g to news reporting out of Shanghai, People’s Republic of China, by NewsRx edito rs, research stated, “The motion planning task of the manipulator in a dynamic e nvironment is relatively complex.” Financial supporters for this research include National Key Research And Develop ment Program of China. Our news correspondents obtained a quote from the research from Shanghai Ocean U niversity: “This paper uses the improved Soft Actor Critic Algorithm (SAC) with the maximum entropy advantage as the benchmark algorithm to implement the motion planning of the manipulator. In order to solve the problem of insufficient robu stness in dynamic environments and difficulty in adapting to environmental chang es, it is proposed to combine Euclidean distance and distance difference to impr ove the accuracy of approaching the target. In addition, in order to solve the p roblem of non-stability and uncertainty of the input state in the dynamic enviro nment, which leads to the inability to fully express the state information, we p ropose an attention network fused with Long Short-Term Memory (LSTM) to improve the SAC algorithm.”
Shanghai Ocean UniversityShanghaiPeo ple’s Republic of ChinaAsiaAlgorithmsEmerging TechnologiesMachine Learni ngRoboticsRobots
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