Locomotion control of a rigid-soft coupled snake robot in multiple environments

Xuanyi Zhou , Yuqiu Zhang , Zhiwei Qiu , Zhecheng Shan , Shibo Cai , Guanjun Bao

Biomimetic Intelligence and Robotics ›› 2024, Vol. 4 ›› Issue (2) : 100148 -100148.

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Biomimetic Intelligence and Robotics ›› 2024, Vol. 4 ›› Issue (2) : 100148 -100148. DOI: 10.1016/j.birob.2024.100148
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Locomotion control of a rigid-soft coupled snake robot in multiple environments

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Abstract

The versatile motion capability of snake robots offers themselves robust adaptability in varieties of challenging environments where traditional robots may be incapacitated. This study reports a novel flexible snake robot featuring a rigid-flexible coupling structure and multiple motion gaits. To better understand the robot’s behavior, a bending model for the soft actuator is established. Furthermore, a dynamic model is developed to map the relationship between the input air pressure and joint torque, which is the model base for controlling the robot effectively. Based on the wave motion generated by the joint coupling direction function in different planes, multiple motion gait planning methods of the snake-like robot are proposed. In order to evaluate the adaptability and maneuverability of the developed snake robot, extensive experiments were conducted in complex environments. The results demonstrate the robot’s effectiveness in navigating through intricate settings, underscoring its potential for applications in various fields.

Keywords

Snake robot / Rigid-flexible coupled / Soft actuator / Motion gait analysis

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Xuanyi Zhou, Yuqiu Zhang, Zhiwei Qiu, Zhecheng Shan, Shibo Cai, Guanjun Bao. Locomotion control of a rigid-soft coupled snake robot in multiple environments. Biomimetic Intelligence and Robotics, 2024, 4(2): 100148-100148 DOI:10.1016/j.birob.2024.100148

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Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research was financially supported by the Joint Fund of National Natural Science Foundation of China with Shenzhen City (U2013212) and the National Key R&D Program of China (2020YFB1313001).

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