Open Access

ARTICLE

Motion-Planning Algorithm for a Hyper-Redundant Manipulator in Narrow Spaces

by Lei Zhang^1,2,*, Shouzhi Huang^1,2, Zhaocai Du³, Guangyao Ouyang^1,2, Heping Chen⁴

1 Faculty of Mechanical Engineering & Automation, Zhejiang Sci-Tech University, Hangzhou, 310018, China
2 Key Laboratory of Transplanting Equipment and Technology of Zhejiang Province, Hangzhou, 310018, China
3 Aeronautical Key Laboratory for Digital Manufacturing Technology, AVIC Manufacturing Technology Institute, Beijing, 100024, China
4 Ingram School of Engineering, Texas State University, San Marcos, Texas, USA

* Corresponding Author: Lei Zhang. Email:

Computers, Materials & Continua 2022, 72(3), 4817-4832. https://doi.org/10.32604/cmc.2022.026845

Received 05 January 2022; Accepted 01 March 2022; Issue published 21 April 2022

Abstract

In this study, a hyper-redundant manipulator was designed for detection and searching in narrow spaces for aerospace and earthquake rescue applications. A forward kinematics equation for the hyper-redundant manipulator was derived using the homogeneous coordinate transformation method. Based on the modal function backbone curve method and the known path, an improved modal method for the backbone curves was proposed. First, the configuration of the backbone curve for the hyper-redundant manipulator was divided into two parts: a mode function curve segment of the mode function and a known path segment. By changing the discrete points along the known path, the backbone curve for the manipulator when it reached a specified path point was dynamically obtained, and then the joint positions of the manipulator were fitted to the main curve by dichotomy. Combined with engineering examples, simulation experiments were performed using the new algorithm to extract mathematical models for external narrow space environments. The experimental results showed that when using the new algorithm, the hyper-redundant manipulator could complete the tasks of passing through curved pipes and moving into narrow workspaces. The effectiveness of the algorithm was also proven by these experiments.

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