Chinese Journal of Mechanical Engineering >

2018 , Vol. 31 >Issue 1: 11 - 11

DOI: https://doi.org/10.1186/s10033-018-0215-8

Mechanism and Robotics

Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary Control

  • Ran Liu ,
  • Yan-An Yao ,
  • Wan Ding ,
  • Xiao-Ping Liu
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  • 1. School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China;
    2. Department of Mechanism Theory and Dynamics of Machines, RWTH Aachen University, 52072 Aachen, Germany;
    3. Department of Systems and Computer Engineering, Carleton University, Ottawa, ONK1 S5B6, Canada

收稿日期: 2016-04-04

  网络出版日期: 2019-07-23

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Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary Control

  • Ran Liu ,
  • Yan-An Yao ,
  • Wan Ding ,
  • Xiao-Ping Liu
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  • 1. School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing 100044, China;
    2. Department of Mechanism Theory and Dynamics of Machines, RWTH Aachen University, 52072 Aachen, Germany;
    3. Department of Systems and Computer Engineering, Carleton University, Ottawa, ONK1 S5B6, Canada

Received date: 2016-04-04

  Online published: 2019-07-23

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摘要

Locomotion and manipulation optimization is essential for the performance of tetrahedron-based mobile mechanism. Most of current optimization methods are constrained to the continuous actuated system with limited degree of freedom (DOF), which is infeasible to the optimization of binary control multi-DOF system. A novel optimization method using for the locomotion and manipulation of an 18 DOFs tetrahedron-based mechanism called 5-TET is proposed. The optimization objective is to realize the required locomotion by executing the least number of struts. Binary control strategy is adopted, and forward kinematic and tipping dynamic analyses are performed, respectively. Based on a developed genetic algorithm (GA), the optimal number of alternative struts between two adjacent steps is obtained as 5. Finally, a potential manipulation function is proposed, and the energy consumption comparison between optimal 5-TET and the traditional wheeled robot is carried out. The presented locomotion optimization and manipulation planning enrich the research of tetrahedron-based mechanisms and provide the instruction to the successive locomotion and operation planning of multi-DOF mechanisms.

关键词： Tetrahedron-based mobile mechanism; Binary control; GA; Locomotion optimization; Manipulation planning

本文引用格式

Ran Liu , Yan-An Yao , Wan Ding , Xiao-Ping Liu . Locomotion Optimization and Manipulation Planning of a Tetrahedron-Based Mobile Mechanism with Binary Control[J]. Chinese Journal of Mechanical Engineering, 2018 , 31(1) : 11 -11 . DOI: 10.1186/s10033-018-0215-8

Abstract

Locomotion and manipulation optimization is essential for the performance of tetrahedron-based mobile mechanism. Most of current optimization methods are constrained to the continuous actuated system with limited degree of freedom (DOF), which is infeasible to the optimization of binary control multi-DOF system. A novel optimization method using for the locomotion and manipulation of an 18 DOFs tetrahedron-based mechanism called 5-TET is proposed. The optimization objective is to realize the required locomotion by executing the least number of struts. Binary control strategy is adopted, and forward kinematic and tipping dynamic analyses are performed, respectively. Based on a developed genetic algorithm (GA), the optimal number of alternative struts between two adjacent steps is obtained as 5. Finally, a potential manipulation function is proposed, and the energy consumption comparison between optimal 5-TET and the traditional wheeled robot is carried out. The presented locomotion optimization and manipulation planning enrich the research of tetrahedron-based mechanisms and provide the instruction to the successive locomotion and operation planning of multi-DOF mechanisms.

Key words： Tetrahedron-based mobile mechanism; Binary control; GA; Locomotion optimization; Manipulation planning

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