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Switchable task-priority framework for combining human-demonstrated and inverse kinematics tasks

机译:可切换的任务优先级框架,用于结合人类演示和逆向运动学任务

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We propose an approach that combines human demonstrated posture-control skill defined by the motion in the lower limb joints with an inverse kinematics solution of an arbitrary hand motion. The posture-control skill for humanoid robot was obtained through the human-in-the-loop teaching approach. The collected data during the teaching phase was used to approximate functional relation between the state of the robot's centre-of-pressure and the appropriate motion in the joints of the leg. The motion of the robot's hand was prescribed using the inverse kinematic solution. The posture-control skill and the motion of the hand were combined together using the task priority resolution strategy. We tested our approach with an experiment where the humanoid robot had to spin a spindle device with the hand and simultaneously maintain balance in the presence of external perturbations. In addition, we propose an upgrade that allows switching of control over the leg joints between arm task and posture-control task.
机译:我们提出了一种方法,该方法结合了人类通过下肢关节运动定义的已证明的姿势控制技能与任意手部运动的逆运动学解决方案。通过环人教学法获得了类人机器人的姿势控制技能。在教学阶段收集的数据用于估计机器人的压力中心状态与腿部关节的适当运动之间的功能关系。使用逆运动学解来规定机器人手的运动。使用任务优先级解析策略将姿势控制技能和手部动作结合在一起。我们通过一个实验来测试我们的方法,在该实验中,类人机器人必须用手旋转主轴设备,并同时在存在外部干扰的情况下保持平衡。此外,我们提出了一种升级方案,允许在手臂任务和姿势控制任务之间切换对腿部关节的控制。

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