Design and analysis of a novel tendon-driven continuum robotic dolphin.

Journal: Bioinspiration & biomimetics
PMID:

Abstract

In this paper, a novel continuum robotic dolphin termed 'ConRoDolI' is proposed and developed. The biomimetic robot features dual tendon driving continuum mechanisms that are utilized to replicate the twisting and bending motions of the dolphin's caudal vertebrae and thoracic vertebrae. More importantly, a central pattern generator based kinematics is analyzed to yield stable dolphin-like swimming. In the meantime, the relationship between the backbone shape and both the tendon length as well as position and orientation are explored. Furthermore, multimodal swimming gaits are designed to pave the way for a three-dimensional (3D) swimming decoupling solution, involving forwarding swimming, multiple yaw patterns, and multiple pitch patterns. All of these endow the robotic dolphin with 3D maneuverability. Finally, extensive experiments demonstrate the feasibility of the proposed biomimetic mechatronic design and control approach. The forward swimming speed is 0.44 body lengths per second (BL/s). The steering radius of the robot is about 0.11 BL with an angular velocity of 10°/s and the diving speed is about 0.13 BL/s. The average propulsion efficiency is about 0.6 with the maximum is over 0.8. The obtained results shed light on the improvement of aquatic maneuverability associated with new-concept underwater vehicles.

Authors

  • Jincun Liu
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, People's Republic of China.
  • Chi Zhang
    Department of Thoracic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Zhenna Liu
    Shandong Labor Vocational and Technical College, Jinan 250022, People's Republic of China.
  • Ran Zhao
    College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.
  • Dong An
  • Yaoguang Wei
    College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, People's Republic of China.
  • Zhengxing Wu
    School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China.
  • Junzhi Yu
    Institute of Automation, Chinese Academy of Sciences, Beijing 100190, PR China. Electronic address: junzhi.yu@ia.ac.cn.