快速行军广场的动觉教学

Javier V. Gómez, David Álvarez, S. Garrido, L. Moreno
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引用次数: 12

摘要

提出了一种新的基于快速行进广场(FM2)的机器人学习技术。这种方法,我们称之为FM学习,是基于将之前的经验结合到机器人的路径规划系统中,考虑到通过动觉教学教给机器人的路径,即手动引导机器人通过期望的路径。该方法将运动视为一个非线性自主动力系统,保证了目标点的路径规划始终是全局渐近稳定系统。该算法的几个参数可以通过调整来获得学习系统的不同行为。该方法已通过一组仿真进行了评估,并在移动机械手Manfred V2中进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kinesthetic teaching via Fast Marching Square
This paper presents a novel robotic learning technique based on Fast Marching Square (FM2). This method, which we have called FM Learning, is based on incorporating previous experience to the path planning system of the robot by taking into account paths taught to the robot via kinesthetic teaching, this is, guiding manually the robot through the desired path. The method proposed ensures that the path planning is always a globally asymptotically stable system at the target point, considering the motion as a nonlinear autonomous dynamical system. The few parameters the algorithm has can be tuned to get different behaviours of the learning system. The method has been evaluated through a set of simulations and also tested in the mobile manipulator Manfred V2.
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