首页|Researchers from Swiss Federal Institute of Technology Lausanne Describe Finding s in Robotics (Robust Quadruped Jumping Via Deep Reinforcement Learning)
Researchers from Swiss Federal Institute of Technology Lausanne Describe Finding s in Robotics (Robust Quadruped Jumping Via Deep Reinforcement Learning)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Robotic s. According to news reporting from Lausanne,Switzerland, by NewsRx journalists , research stated, “In this paper, we consider a general task of jumpingvarying distances and heights for a quadrupedal robot in noisy environments, such as of f of uneventerrain and with variable robot dynamics parameters. To accurately j ump in such conditions, we propose aframework using deep reinforcement learning that leverages and augments the complex solution of nonlineartrajectory optimi zation for quadrupedal jumping.”
LausanneSwitzerlandEuropeEmerging TechnologiesMachine LearningReinforcement LearningRobotRoboticsSwiss F ederal Institute of Technology Lausanne
NETL
NSTL
