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A Dynamical System Approach for Softly Catching a Flying Object: Theory and Experiment

机译:一种轻柔捕捉飞行物体的动力学系统方法:理论与实验

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Catching a fast flying object is particularly challenging as it consists of two tasks: extremely precise estimation of the object's motion and control of the robot's motion. Any small imprecision may lead the fingers to close too abruptly and let the object fly away from the hand before closing. We present a strategy to overcome for sensorimotor imprecision by introducing softness in the catching approach. catching consists of having the robot moves with the object for a short period of time, so as to leave more time for the fingers to close on the object. We use a dynamic system-based control law to generate the appropriate reach and follow motion, which is expressed as a linear parameter varying (LPV) system. We propose a method to approximate the parameters of LPV systems using Gaussian mixture models, based on a set of kinematically feasible demonstrations generated by an offline optimal control framework. We show theoretically that the resulting DS will intercept the object at the point, at the right with the desired . Stability and convergence of the approach are assessed through Lyapunov stability theory. The proposed method is validated systematically to catch three objects that generate elastic contacts and demonstrate important improvement over a catching approach.
机译:捕捉快速飞行的物体特别具有挑战性,因为它包含两个任务:极其精确地估计物体的运动和控制机器人的运动。任何小的不精确度都可能导致手指突然闭合,并在闭合之前让物体从手上飞走。我们提出了一种通过在捕获方法中引入柔软性来克服感觉运动不精确的策略。捕获包括让机器人在短时间内与对象一起移动,以便留出更多时间让手指闭合在对象上。我们使用基于动态系统的控制定律来生成适当的到达和跟随运动,将其表示为线性参数变化(LPV)系统。基于离线优化控制框架产生的一组在运动学上可行的演示,我们提出了一种使用高斯混合模型近似LPV系统参数的方法。从理论上讲,我们证明了生成的DS将在右侧的所需点处截取对象。通过Lyapunov稳定性理论评估了该方法的稳定性和收敛性。所提出的方法经过系统验证,可以捕获三个产生弹性接触的物体,并证明了在捕获方法上的重要改进。

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