A Planning and Control Scheme for the Run-and-Jump Motion of a Wheeled Bipedal Robot Considering Dynamic Constraints

Wheeled bipedal robots (WBRs) have recently drawn great attention due to their high movement efficiency and remarkable terrain adaptability. With the utilization of legs, they can adjust postures on uneven ground, as well as jump over obstacles or gaps. Nevertheless, compared to the extensive strategies for the balance control, the jumping motion of the WBRs has not received adequate research. In view of this, we propose a comprehensive planning and control scheme for the run-and-jump motion of WBRs, facilitating a seamless transition between running and jumping modalities. The motion is meticulously dissected into three stages: preparation, flight, and recovery, each characterized by a set of critical states at key transition points. These states are designed following an in-depth analysis of the run-and-jump objectives, ensuring compliance with the system dynamic constraints and consideration of the motor capacities. This methodology formulates an optimization problem, yielding reference trajectories that are pivotal for the execution of the run-and-jump motion. Based on reference trajectories, a customized motion library for the different run-and-jump motions is established, which alleviates the computational burden and ensures the versatility of the run-and-jump motion. Furthermore, the tracking controller, attitude adjustment controller, and impedance controller are developed separately to ensure the smoothness and stability of the overall run-and-jump motion. The performance and effectiveness of the proposed scheme are first investigated through physical simulation and further validated by convincing hardware experiments.

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Publication Details

Journal
IEEE Transactions on Industrial Electronics
Published
2025-01-01
DOI
https://doi.org/10.1109/tie.2025.3566751
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

A Planning and Control Scheme for the Run-and-Jump Motion of a Wheeled Bipedal Robot Considering Dynamic Constraints

Haixin Cao, Biao Lu, Yongchun Fang, Shuang Tang et al.
IEEE Transactions on Industrial Electronics
Robotic Path Planning Algorithms
article

A Planning and Control Scheme for the Run-and-Jump Motion of a Wheeled Bipedal Robot Considering Dynamic Constraints

Haixin Cao, Biao Lu, Yongchun Fang, Shuang Tang, Yunsong Hao
article en

Abstract

Wheeled bipedal robots (WBRs) have recently drawn great attention due to their high movement efficiency and remarkable terrain adaptability. With the utilization of legs, they can adjust postures on uneven ground, as well as jump over obstacles or gaps. Nevertheless, compared to the extensive strategies for the balance control, the jumping motion of the WBRs has not received adequate research. In view of this, we propose a comprehensive planning and control scheme for the run-and-jump motion of WBRs, facilitating a seamless transition between running and jumping modalities. The motion is meticulously dissected into three stages: preparation, flight, and recovery, each characterized by a set of critical states at key transition points. These states are designed following an in-depth analysis of the run-and-jump objectives, ensuring compliance with the system dynamic constraints and consideration of the motor capacities. This methodology formulates an optimization problem, yielding reference trajectories that are pivotal for the execution of the run-and-jump motion. Based on reference trajectories, a customized motion library for the different run-and-jump motions is established, which alleviates the computational burden and ensures the versatility of the run-and-jump motion. Furthermore, the tracking controller, attitude adjustment controller, and impedance controller are developed separately to ensure the smoothness and stability of the overall run-and-jump motion. The performance and effectiveness of the proposed scheme are first investigated through physical simulation and further validated by convincing hardware experiments.

IEEE Transactions on Industrial Electronics
Nankai University (CN)
Sustainable cities and communities
Openalex Percentile: Top 91%
Robotic Path Planning Algorithms
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