Energy-optimal motion planning of a biped pole-climbing robot with kinodynamic constraints. Issue 3 (21st May 2018)

• Record Type: Journal Article
• Authors: Zhou, Xuefeng; Jiang, Li; Guan, Yisheng; Zhu, Haifei; Huang, Dan; Cheng, Taobo; Zhang, Hong
• Is Part Of: Industrial robot. Volume 45:Issue 3(2018)
• Page Start: 343
• Page End: 353
• Publication Date: 2018-05-21
• Subjects: Motion planning -- Climbing robots -- Energy optimization -- Kinodynamic constraints; Robots, Industrial -- Periodicals; Machinery in the workplace -- Periodicals; 629.892
• DOI: 10.1108/IR-11-2017-0200
• Languages: English
• ISSNs: 0143-991X

Abstract

Abstract : Purpose: Applications of robotic systems in agriculture, forestry and high-altitude work will enter a new and huge stage in the near future. For these application fields, climbing robots have attracted much attention and have become one central topic in robotic research. The purpose of this paper is to propose an energy-optimal motion planning method for climbing robots that are applied in an outdoor environment. Design/methodology/approach: First, a self-designed climbing robot named Climbot is briefly introduced. Then, an energy-optimal motion planning method is proposed for Climbot with simultaneous consideration of kinematic constraints and dynamic constraints. To decrease computing complexity, an acceleration continuous trajectory planner and a path planner based on spatial continuous curve are designed. Simulation and experimental results indicate that this method can search an energy-optimal path effectively. Findings: Climbot can evidently reduce energy consumption when it moves along the energy-optimal path derived by the method used in this paper. Research limitations/implications: Only one step climbing motion planning is considered in this method. Practical implications: With the proposed motion planning method, climbing robots applied in an outdoor environment can commit more missions with limit power supply. In addition, it is also proved that this motion planning method is effective in a complicated obstacle environment with collision-free constraint. Originality/value: The main contribution of this paper is that it establishes a two-planner system to solve the complex motion planning problem with kinodynamic constraints.