Hierarchical collision-free motion planning method for biped truss-climbing robots

Biped truss climbing robots (BTCRs) are employed to perform high-rise tasks within truss environments, benefiting from their superior transition capabilities and flexible mobility. However, the intricate geometry of these structures poses challenges for robot navigation and operation. To tackle this issue, this paper proposes a novel BTCRs climbing path planning framework based on a progressive multi-layer architecture. The robot’s transition regions between adjacent members are determined efficiently by unfolding three-dimensional truss members onto two-dimensional planes and discretizing them. Initially, leveraging transition analysis, a global truss member route using graph search methods is generated. Subsequently, a mathematical optimization model is introduced to determine transition grips along the global route, minimizing the total number of grips. Finally, the single-step path planner employs an improved rapidly-exploring random tree (RRT)-connect algorithm, guaranteeing collision-free motion between adjacent grips. By integrating these three layers, the framework demonstrates the feasibility and effectiveness of the proposed analysis and algorithms for climbing path planning in simulation tests, using a self-developed BTCR, Climbot.

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Publication Details

Journal
Transactions of the Institute of Measurement and Control
Published
2025-03-22
DOI
https://doi.org/10.1177/01423312241309411
Primary Topic
Robotic Locomotion and Control
Type
article
Field-Weighted Citation Impact
0.00

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article

Hierarchical collision-free motion planning method for biped truss-climbing robots

Ming Nie, Shangbiao Wei, Haifei Zhu, Yisheng Guan et al.
Transactions of the Institute of Measurement and Control
Robotic Locomotion and Control
article

Hierarchical collision-free motion planning method for biped truss-climbing robots

Ming Nie, Shangbiao Wei, Haifei Zhu, Yisheng Guan, Shichao Gu, Xiaoguang Liu, Xuefeng Zhou
article en

Abstract

Biped truss climbing robots (BTCRs) are employed to perform high-rise tasks within truss environments, benefiting from their superior transition capabilities and flexible mobility. However, the intricate geometry of these structures poses challenges for robot navigation and operation. To tackle this issue, this paper proposes a novel BTCRs climbing path planning framework based on a progressive multi-layer architecture. The robot’s transition regions between adjacent members are determined efficiently by unfolding three-dimensional truss members onto two-dimensional planes and discretizing them. Initially, leveraging transition analysis, a global truss member route using graph search methods is generated. Subsequently, a mathematical optimization model is introduced to determine transition grips along the global route, minimizing the total number of grips. Finally, the single-step path planner employs an improved rapidly-exploring random tree (RRT)-connect algorithm, guaranteeing collision-free motion between adjacent grips. By integrating these three layers, the framework demonstrates the feasibility and effectiveness of the proposed analysis and algorithms for climbing path planning in simulation tests, using a self-developed BTCR, Climbot.

Transactions of the Institute of Measurement and ControlVol. 48(6)
Guangdong University of Technology (CN), Guangdong Academy of Sciences (CN), Guangzhou Maritime College (CN), Guangdong Institute of Intelligent Manufacturing (CN), China Southern Power Grid (China) (CN)
China Postdoctoral Science Foundation, Science and Technology Planning Project of Guangdong Province, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 95%
Robotic Locomotion and Control
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