论文标题

通过刚性多体模型预测机器人臂的影响后速度:一项实验研究

Predicting the Post-Impact Velocity of a Robotic Arm via Rigid Multibody Models: an Experimental Study

论文作者

Aouaj, Ilias, Padois, Vincent, Saccon, Alessandro

论文摘要

准确的影响后速度预测对于建立对机器人的影响感知的操纵策略至关重要,在这种情况下,在非零速度下有意建立了触点,以模仿人类操纵能力在动态抓握和推动物体中。从有意影响刚性表面的7DOF扭矩控制机器人的记录动态响应开始,我们研究了预测影响后影响后速度的可能性和准确性。 The velocity prediction is obtained by means of an impact map, derived using the framework of nonsmooth mechanics, that makes use of the known rigid-body robot model and the assumption of a frictionless inelastic impact.The main contribution is proposing a methodology that allows for a meaningful quantitative comparison between the recorded post-impact data, that exhibits a damped oscillatory response after the impact, and the post-impact velocity prediction通过易于可用的刚体机器人模型得出,该模型没有振荡,这是通常通过主流机器人模拟器软件获得的振荡。从预测准确性方面,这种新方法的结果是有希望的,因此与影响感知机器人控制的不断增长的领域有关。记录的影响数据(18个实验)与用于生成定量比较的数值例程公开可用,以进一步刺激该领域的兴趣/研究。

Accurate post-impact velocity predictions are essential in developing impact-aware manipulation strategies for robots, where contacts are intentionally established at non-zero speed mimicking human manipulation abilities in dynamic grasping and pushing of objects. Starting from the recorded dynamic response of a 7DOF torque-controlled robot that intentionally impacts a rigid surface, we investigate the possibility and accuracy of predicting the post-impact robot velocity from the pre-impact velocity and impact configuration. The velocity prediction is obtained by means of an impact map, derived using the framework of nonsmooth mechanics, that makes use of the known rigid-body robot model and the assumption of a frictionless inelastic impact.The main contribution is proposing a methodology that allows for a meaningful quantitative comparison between the recorded post-impact data, that exhibits a damped oscillatory response after the impact, and the post-impact velocity prediction derived via the readily available rigid-body robot model, that presents no oscillations and that is the one typically obtained via mainstream robot simulator software. The results of this new approach are promising in terms of prediction accuracy and thus relevant for the growing field of impact-aware robot control. The recorded impact data (18 experiments) is made publicly available, together with the numerical routines employed to generate the quantitative comparison, to further stimulate interest/research in this field.

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