A Motion Generation Method for Articulated Manipulators Using Linear Mapping Matrices Calculated by Neural Networks

A Motion Generation Method for Articulated Manipulators Using Linear Mapping Matrices Calculated by Neural Networks
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一种利用神经网络计算的线性映射矩阵的关节机械臂运动生成方法

DOI:
10.1109/case49439.2021.9551436
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发表时间:
2021
期刊:
Proc. of IEEE 17th International Conference on Automation Science and Engineering
影响因子:
--
通讯作者:
Kimitoshi Yamazaki
Kimitoshi Yamazaki
中科院分区:
--
文献类型:
--
作者:
石田直輝,窪田智之,伊藤圭基,白松(磯口)知世,高橋宏知;Kimitoshi Yamazaki

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本文提出了一种关节型机器人运动生成的方法。在该方法中,运动序列是基于过去的运动经验生成的。大致的程序如下。机械手预先完成各种到达动作,并将这些经验存储为末端执行器位姿、关节角度、环境地图等,当给定新的目标末端执行器位姿时,机械手有效地利用过去的经验生成新的运动序列。该方法包括两个阶段:相似经验搜索和运动修改。在后一阶段中,利用神经网络来计算修改移动量。它确保了一定程度的轨迹再现性。通过对平面和三维机器人的仿真,证明了该方法的有效性。
In this paper, a method of motion generation for articulated manipulators is proposed. In this method, motion sequence is generated based on past motion experience. The rough procedure is as follows. Various reaching motions are performed by the manipulator in advance, and then, these experiences are stored by the manipulator as end-effector poses, joint angles, environment map, and so on. Then, the manipulator generates a new motion sequence by efficiently using the past experiences when a new target end-effector pose is given. The proposed method comprises two phases: similar experience search and motion modification. In the latter phase, a neural network is utilized to calculate the amount of modification movement. It ensures a certain level of trajectory reproducibility. The effectiveness of the proposed method is proven via simulation considering planar and 3D manipulators.
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