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Volume 10 Issue 9
Sep.  2023

IEEE/CAA Journal of Automatica Sinica

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    CiteScore: 23.5, Top 2% (Q1)
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Article Contents
D. F. Li, Y. L. Zhang, P. Li, R. Law, Z. R. Xiang, X. Xu, L. M. Zhu, and E. Q. Wu, “Position errors and interference prediction-based trajectory tracking for snake robots,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 9, pp. 1810–1821, Sept. 2023. doi: 10.1109/JAS.2023.123612
Citation: D. F. Li, Y. L. Zhang, P. Li, R. Law, Z. R. Xiang, X. Xu, L. M. Zhu, and E. Q. Wu, “Position errors and interference prediction-based trajectory tracking for snake robots,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 9, pp. 1810–1821, Sept. 2023. doi: 10.1109/JAS.2023.123612

Position Errors and Interference Prediction-Based Trajectory Tracking for Snake Robots

doi: 10.1109/JAS.2023.123612
Funds:  This work was supported in part by the National Natural Science Foundation of China (T2325018, U2241228, 62273019, 61825305, U1933125, 72192820, 72192824, 62171274), the China Postdoctoral Science Foundation (2022M710093), and the Open Project Program of the Key Laboratory for Agricultural Machinery Intelligent Control and Manufacturing of Fujian Education Institutions (AMICM202102)
More Information
  • This work presents a trajectory tracking control method for snake robots. This method eliminates the influence of time-varying interferences on the body and reduces the offset error of a robot with a predetermined trajectory. The optimized line-of-sight (LOS) guidance strategy drives the robot’s steering angle to maintain its anti-sideslip ability by predicting position errors and interferences. Then, the predictions of system parameters and viscous friction coefficients can compensate for the joint torque control input. The compensation is adopted to enhance the compatibility of a robot within ever-changing environments. Simulation and experimental outcomes show that our work can decrease the fluctuation peak of the tracking errors, reduce adjustment time, and improve accuracy.


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    • This work optimizes the LOS guidance law through predicted position errors and interference variables. This method applies anti-sideslip ability to a snake robot, which improves the tracking accuracy of the body to the desired path
    • This work uses model parameter and friction coefficient predictions of a snake robot to compensate for system input by eliminating the joint’s jitter
    • This work reduces the fluctuation peak and convergence time of errors and enhances the adaptability of a snake robot to environmental shifts


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