基于记忆的运动环境识别与有效运动规划控制

S. Kawamura, M. Nakagawa
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引用次数: 4

摘要

指出了基于记忆的机器人运动控制方案的重要性。在基于内存的控制方案中,所有关于机器人运动的数值都存储在数字计算机的内存中,而不是对机器人运动和机器人周围的环境进行建模。提出了一种适用于未知环境下机器人运动的基于记忆的控制方案。在所提出的控制方案的第一步,机器人通过测试运动(即机器人的实际运动)来识别未知环境。因此,机器人对运动环境的认识就像数字计算机存储器中的一种地图。第二步,利用测试运动得到的环境图中的路径规划技术,使机器人形成能够实现有效运动的运动模式。通过机器人在水中和地面上移动的两个实验结果证明了所提出的基于记忆的控制方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Memory-based control for recognition of motion environment and planning of effective locomotion
Points out the importance of memory-based schemes for motion control of robots. In memory-based control schemes, all values concerning robot motion are stored in memory of digital computers instead of modeling the robot motion and the environment around the robot. The authors propose a memory-based control scheme which is suitable for locomotion of robots in unknown environment. At the first step of the proposed control scheme, a robot recognizes the unknown environment through test motions which mean actual movement of the robot. As a result, the robot has knowledge of the motion environment as a kind of map in the memory of digital computers. At the second step, by using path planning techniques in the environment maps obtained by the test motions, the robot forms a motion pattern which can realize effective locomotion. The effectiveness of the proposed memory-based control scheme is demonstrated through two experimental results in which robots move in the water and on the ground.<>
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