首页|New Findings from Beijing Institute of Technology Update Understanding of Roboti cs (Motion Transition Under Urgent Change of Target Step-stone During Three-dime nsional Biped Walking)
New Findings from Beijing Institute of Technology Update Understanding of Roboti cs (Motion Transition Under Urgent Change of Target Step-stone During Three-dime nsional Biped Walking)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news reporting originating in Beijing, People's Republic of China, by NewsRx journalists, research stated, "Controlling a biped robot to wa lk through rough terrains is crucial to the robot's field application. For a hum an in the workplace, the ability to flexibly transfer motion while walking in so me urgent circumstances is necessary." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from the Beijing Institute of Technology, "Explicitly, the according scenario can be dodging an approachin g object or instantly modifying the target place to step on. The function is als o important for humanoid robot workers. Therefore, we proposed a walking control framework that achieves three-dimensional (3-D) walking and transfers the whole body motion when the target stepping location is urgently changed. The proposed framework contains a motion planner which outputs the desired center of mass (C oM) and center of pressure (CoP) trajectories in 3-D space and a hierarchical wh ole body controller (WBC) that outputs corresponding whole body joints' trajecto ries. In the motion planner, the CoM jerk for each loop is calculated by the Lin ear-Quadratic- Tracker (LQT), a variation of the Linear-Quadratic-Regulator (LQR) . The LQT coefficients adapt to the adjusted step length, making the desired CoM and CoP trajectories respond flexibly to the change of target step-stone. In WB C, three levels of tasks are defined, which meet dynamic, kinematic, and viable contact constraints, respectively. The optimal joints' angular accelerations are obtained by exploiting the nullspace of the first two levels tasks and by quadr atic programming (QP) for the third-level task." According to the news reporters, the research concluded: "In the simulations, ou r method is demonstrated to be effective for the robot to transfer the motion un der urgent change of the target step-stone." This research has been peer-reviewed.
BeijingPeople's Republic of ChinaAsi aEmerging TechnologiesMachine LearningRobotRoboticsBeijing Institute o f Technology
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