首页|Tianjin University of Commerce Researchers Report Recent Findings in Robotics (Energy Consumption Minimization of Quadruped Robot Based on Reinforcement Learning of DDPG Algorithm)
Tianjin University of Commerce Researchers Report Recent Findings in Robotics (Energy Consumption Minimization of Quadruped Robot Based on Reinforcement Learning of DDPG Algorithm)
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Research findings on robotics are discussed in a new report. According to news reporting out of Tianjin, People's Republic of China, by NewsRx editors, research stated, “Energy consumption is one of the most critical factors in determining the kinematic performance of quadruped robots.” Financial supporters for this research include Chunhui Project Foundation of The Education Department of China. The news editors obtained a quote from the research from Tianjin University of Commerce: “However, existing research methods often encounter challenges in quickly and efficiently reducing the energy consumption associated with quadrupedal robotic locomotion. In this paper, the deep deterministic policy gradient (DDPG) algorithm was used to optimize the energy consumption of the Cyber Dog quadruped robot. Firstly, the kinematic and energy consumption models of the robot were established. Secondly, energy consumption was optimized by reinforcement learning using the DDPG algorithm. The optimized plantar trajectory was then compared with two common plantar trajectories in simulation experiments, with the same period and the number of synchronizations but varying velocities. Lastly, real experiments were conducted using a prototype machine to validate the simulation data.”
Tianjin University of CommerceTianjinPeople's Republic of ChinaAsiaAlgorithmsEmerging TechnologiesMachine LearningReinforcement LearningRobotRobotics
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