Optimization of fluent approach and grasp motions
Optimization of fluent approach and grasp motions
复制标题
优化流畅的接近和抓取动作
DOI：
--
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
C. Goerick
中科院分区：
文献类型：
--
作者：
M. Gienger;Marc Toussaint;Nikolay Jetchev;A. Bendig;C. Goerick
产生接近、抓取和抬起物体的流畅运动包括许多通常单独解决的问题。现有的一些研究侧重于基于力闭合准则的最终抓取姿态的优化，而忽略了接近该抓取所需的运动。其他研究专门研究运动优化，包括避免碰撞准则，但通常不考虑后续抓取作为优化问题的一部分。在本文中，我们的目标是将现有的抓取优化技术、轨迹优化技术和基于吸引子的运动表示技术结合起来，形成一个全面的框架，使我们能够有效地计算一个流畅的方法和抓取运动。仿真研究和仿人机器人实验表明了该方法的可行性。
Generating a fluent motion of approaching, grasping and lifting an object comprises a number of problems which are typically tackled separately. Some existing research specializes on the optimization of the final grasp posture based on force closure criteria neglecting the motion necessary to approach this grasp. Other research specializes on motion optimization including collision avoidance criteria, but typically not considering the subsequent grasp as part of the optimization problem. In this paper we aim to combine existing techniques for grasp optimization, trajectory optimization, and attractor-based movement representation, into a comprehensive framework that allows us to efficiently compute a fluent approach and grasping motion. The feasibility of the proposed approach is shown in simulation studies and experiments with a humanoid robot.