首页|Chengdu University Researcher Details Findings in Robotics (Research on the Moti on Control Strategy of a Lower-Limb Exoskeleton Rehabilitation Robot Using the T win Delayed Deep Deterministic Policy Gradient Algorithm)
Chengdu University Researcher Details Findings in Robotics (Research on the Moti on Control Strategy of a Lower-Limb Exoskeleton Rehabilitation Robot Using the T win Delayed Deep Deterministic Policy Gradient Algorithm)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on robotics are presented in a new rep ort. According to news originating from Chengdu, People's Republic of China, by NewsRx editors, the research stated, "The motion control system of a lower-limb exoskeleton rehabilitation robot (LLERR) is designed to assist patients in lower -limb rehabilitation exercises." Funders for this research include The Sichuan Provincial Regional Innovation Coo peration Project. The news correspondents obtained a quote from the research from Chengdu Universi ty: "This research designed a motion controller for an LLERR-based on the Twin D elayed Deep Deterministic policy gradient (TD3) algorithm to control the lower-l imb exoskeleton for gait training in a staircase environment. Commencing with th e establishment of a mathematical model of the LLERR, the dynamics during its mo vement are systematically described. The TD3 algorithm is employed to plan the m otion trajectory of the LLERR's right-foot sole, and the target motion curve of the hip (knee) joint is deduced inversely to ensure adherence to human physiolog ical principles during motion execution. The control strategy of the TD3 algorit hm ensures that the movement of each joint of the LLERR is consistent with the t arget motion trajectory."
Chengdu UniversityChengduPeople's Re public of ChinaAsiaAlgorithmsEmerging TechnologiesMachine LearningRobo tRobotics
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