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一种用于冗余机器人机械臂运动规划的新型抗噪声避障方案。

A New Noise-Tolerant Obstacle Avoidance Scheme for Motion Planning of Redundant Robot Manipulators.

作者信息

Guo Dongsheng, Xu Feng, Yan Laicheng, Nie Zhuoyun, Shao Hui

机构信息

College of Information Science and Engineering, Huaqiao University, Xiamen, China.

出版信息

Front Neurorobot. 2018 Aug 29;12:51. doi: 10.3389/fnbot.2018.00051. eCollection 2018.

Abstract

Avoiding obstacle(s) is a challenging issue in the research of redundant robot manipulators. In addition, noise from truncation, rounding, and model uncertainty is an important factor that affects greatly the obstacle avoidance scheme. In this paper, based on the neural dynamics design formula, a new scheme with the pseudoinverse-type formulation is proposed for obstacle avoidance of redundant robot manipulators in a noisy environment. Such a scheme has the capability of suppressing constant and bounded time-varying noises, and it is thus termed as the noise-tolerant obstacle avoidance (NTOA) scheme in this paper. Theoretical results are also given to show the excellent property of the proposed NTOA scheme (particularly in noise situation). Based on a PA10 robot manipulator with point and window-shaped obstacles, computer simulation results are presented to further substantiate the efficacy and superiority of the proposed NTOA scheme for motion planning of redundant robot manipulators.

摘要

在冗余机器人操纵器的研究中,避障是一个具有挑战性的问题。此外,截断、舍入和模型不确定性产生的噪声是极大影响避障方案的一个重要因素。本文基于神经动力学设计公式,提出了一种具有伪逆型公式的新方案,用于在噪声环境下冗余机器人操纵器的避障。这种方案具有抑制恒定和有界时变噪声的能力,因此在本文中被称为耐噪声避障(NTOA)方案。还给出了理论结果以表明所提出的NTOA方案的优异性能(特别是在噪声情况下)。基于具有点形和窗口形障碍物的PA10机器人操纵器,给出了计算机仿真结果,以进一步证实所提出的NTOA方案在冗余机器人操纵器运动规划中的有效性和优越性。

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