Wall Deadlock Evasion Control Based on Rotation Radius Adjustment

Shotaro Kojima, Kazunori Ohno, Takahiro Suzuki, Yoshito Okada, Thomas Westfechtel, Satoshi Tadokoro

Research output: Contribution to journalArticlepeer-review

Abstract

This letter describes a wall deadlock evasion method for tracked vehicles. Wall deadlock is a phenomenon where the robot cannot rotate to the commanded direction when it collides with a wall, because the motion is restricted by the wall. The key idea behind solving this problem involves an adjustment of the rotation radius to generate sufficient rotational moment. There are several approaches to generate a rotational moment; however, no previous solution has been established to address this problem by adjusting the rotation radius based on the dynamics of wall deadlock. In this letter, the authors propose a new wall deadlock evasion method based on the sufficient rotation radius estimation. Experimental results show that the robot can generate rotational motion that satisfies conditions expected by the model. The wall deadlock evasion method is implemented and shows improved performance in terms of reproducibility of motion compared with the different approach proposed in our previous work. Wall deadlock evasion provides more choices of motion such as being as close to the obstacles as possible and ensures that the robot can continue locomotion after such motion. By handling wall deadlock, the robots can utilize surrounding walls for motion in situations such as relative positioning or driving in fixed lanes.

Original languageEnglish
Article number8962032
Pages (from-to)1358-1365
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume5
Issue number2
DOIs
Publication statusPublished - 2020 Apr

Keywords

  • Motion control
  • autonomous vehicle navigation
  • dynamics
  • wheeled robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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