Hostname: page-component-848d4c4894-75dct Total loading time: 0 Render date: 2024-05-23T20:45:30.424Z Has data issue: false hasContentIssue false
  • English
  • Français

Autonomous navigation and steering control based on wireless non-wheeled snake robot

Published online by Cambridge University Press:  08 May 2024

Liming Bao Open the ORCID record for Liming Bao [Opens in a new window] ,
Yongjun Sun  and
Zongwu Xie
Liming Bao
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China
Yongjun Sun*
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China
Zongwu Xie
Affiliation:
State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China
*
Corresponding author: Yongjun Sun; Email: sunyongjun@hit.edu.cn
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper mainly studies an autonomous path-planning and real-time path-tracking optimization method for snake robot. Snake robots can perform search and rescue, exploration, and other tasks in a variety of complex environments. Robots with visual sensors such as LiDAR can avoid obstacles in the environment through autonomous navigation to reach the target point. However, in an unstructured environment, the navigation of snake robot is easily affected by the external environment, causing the robot to deviate from the planned path. In order to solve the problem that snake robots are easily affected by environmental factors in unstructured environments, resulting in poor path-following ability, this paper uses the Los algorithm combined with steering control to plan the robot in real time and control the robot’s steering parameters in real time, ensuring that the robot can stably follow the planned path.

Keywords

snake robotautonomous navigationsteering controlpath following
Type
Research Article
Information
Robotica , First View , pp. 1 - 10
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baysal, Y. A. and Altas, I. H., “Adaptive Snake Robot Locomotion in Different Environments,” In: 2020 International Conference on Control, Automation and Diagnosis (ICCAD), Paris, France (2020) pp. 1–6.Google Scholar
Yang, W., Wang, G. and Shen, Y., “Perception-Aware Path Finding and Following of Snake Robot in Unknown Environment,” In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, USA (2020) pp. 5925–5930.Google Scholar
Han, S., Chon, S., Kim, J. Y., Seo, J., Shin, D. G., Park, S., Kim, J. T., Kim, J., Jin, M. and Cho, J., “Snake robot gripper module for search and rescue in narrow spaces,” IEEE Robot Auto Lett 7(2), 1667–1673 (2022).CrossRefGoogle Scholar
Liljebäck, P.. Snake Robots: Modelling, Mechatronics, and Control (Springer, London, 2013).CrossRefGoogle Scholar
Toyoshima, S. and Matsuno, F., “A Study on Sinus-Lifting Motion of a Snake Robot with Energetic Efficiency,” In: 2012 IEEE Inter-national Conference on Robotics and Automation, Saint Paul, USA (2012) pp. 2673–2678.Google Scholar
Prada, E., Valášek, M., Virgala, I., Gmiterko, A., Kelemen, M., Hagara, M. and Lipták, T., “New Approach of Fixation Possibilities Investigation for Snake Robot in the Pipe,” In: 2015 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China (2015) pp. 1204–1210.Google Scholar
Liu, J., Wang, Y., Li, M. and Deng, R., “Joint Linkage and Motion System Design of Pipeline Detecting Snake Robot,” In: 35th Chinese Control and Decision Conference (CCDC), Yichang, China (2023) pp. 1545–1550. doi: 10.1109/CCDC58219.2023.10327219 CrossRefGoogle Scholar
Wang, C., Puranam, V. R., Misra, S. and Venkiteswaran, V. K., “A snake-inspired multi-segmented magnetic soft robot to-wards medical applications,” IEEE Robot Auto Lett 7(2), 5795–5802 (2022).CrossRefGoogle Scholar
Hsu, K. L., “Obstacle avoidance path scheme of snake robot based on bidirectional fast expanding random tree algorithm,” J King Saud Univ - Sci 34(4), 101975 (2022).CrossRefGoogle Scholar
Wang, Z., Chang, J., Li, B., Wang, C. and Liu, C., “Application of Improved Rapidly-exploring Random Trees (RRT) algorithm for Obstacle Avoidance of Snake-like Manipulator,” In: 2020 IEEE International Conference on Mechatronics and Automation (ICMA), Beijing, China (2020) pp. 490–495. doi: 10.1109/ICMA49215.2020.9233573 CrossRefGoogle Scholar
Chen, X. and Jiang, Y., “Three Dimensional Path Planning of Snake-Arm Robot Based on Improved Ant Colony Algorithm,” In: 12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), Baishan, China (2022) pp. 888–892. doi: 10.1109/CYBER55403.2022.9907588 CrossRefGoogle Scholar
Yang, W., Wang, G., Shao, H. and Shen, Y., “Spline Based Curve Path Following of Underactuated Snake Robots,” In: 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada (2019) pp. 5352–5358. doi: 10.1109/ICRA.2019.8793531 CrossRefGoogle Scholar
Xiu, Y., Li, D., Zhang, M., Law, R. and Wu, E. Q., “Anti-sideslip Line of Sight Method-based Path Tracking Control for a Multi-joint Snake Robot,” In: 2022 IEEE International Conference on Networking, Sensing and Control (ICNSC), Shanghai, China (2022) pp. 1–6. doi: 10.1109/ICNSC55942.2022.10004143 CrossRefGoogle Scholar
Takanashi, T., Nakajima, M., Takemori, T. and Tanaka, M., “Obstacle-aided locomotion of a snake robot using piecewise helixes,” IEEE Robot Auto Lett 7(4), 10542–10549 (2022). doi: 10.1109/LRA.2022.3194689.CrossRefGoogle Scholar
Ni, F., Li, Y., Zhou, Y., Zhao, L. and Liu, H., “Design of a Hierarchical Control System for Tetherless Snake Robot,” In: 2019 IEEE International Conference on Mechatronics and Automation (ICMA), Tianjin, China (2019) pp. 1254–1259.Google Scholar
Zhou, Y., Zhang, Y., Ni, F. and Liu, H., “Head-raising method of snake robots based on the Bézier curve,” Robotica 39(3), 503–523 (2021). doi: 10.1017/S0263574720000533.CrossRefGoogle Scholar
He, P., Jin, M. H., Yang, L., Wei, R., Liu, Y. W., Cai, H. G., Liu, H., Seitz, N., Butterfass, J. and Hirzinger, G., “High Performance DSP/FPGA Controller for Implementation of HIT/DLR Dexterous Robot Hand,” In: IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA ‘04, New Orleans, USA (2004) pp. 3397–3402. doi: 10.1109/ROBOT.2004.1308779.CrossRefGoogle Scholar
Tomei, P., “A simple PD controller for robots with elastic joints,” Ieee Trans Automat Contr 36(10), 1208–1213 (1991).CrossRefGoogle Scholar
Wei, X., Yang, C., Kong, L. and Sun, P., “Improved Hector-SLAM Algorithm Based On Data Fusion of LiDAR and IMU for a Wheeled Robot Working in Machining Workshop,” In: 2022 China Automation Congress (CAC), Xiamen, China (2022) pp.2126–2131. doi: 10.1109/CAC57257.2022.10055160.CrossRefGoogle Scholar
Xiu, Y., Li, D., Deng, H., Jiang, S. and Wu, E. Q., “Path-following based on fuzzy line-of-sight guidance for a bionic snake robot with unknowns,” IEEE/ASME Trans Mechatr 28(6), 3167–3179 (2023). doi: 10.1109/TMECH.2023.3254817.CrossRefGoogle Scholar
Bao, L., Sun, Y., Wang, Q. and Xie, Z., “Study on head stabilization control strategy of non-wheeled snake robot based on inertial sensor,” Appl Sci 13(7), 4477 (2023). doi: 10.3390/app13074477.CrossRefGoogle Scholar
Nagla, S., “2D Hector SLAM of Indoor Mobile Robot using 2D Lidar,” In: International Conference on Power, Energy, Control and Transmission Systems (ICPECTS), Chennai, India (2020) pp. 1–4. doi: 10.1109/ICPECTS49113.2020.9336995 CrossRefGoogle Scholar
Kaleem, M. K., Verma, D. and Idrisi, M. J., “Generalization of Line Drawing Algorithm – An Effective Approach to Minimize the Error in the Existing Bresenham’s Line Drawing Algorithm,” In: 2021 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India (2021) pp. 516–521. doi: 10.1109/ESCI50559.2021.9396940 CrossRefGoogle Scholar
Ullah, S. I., Mahmood, T. and Anayatullah, “Autonomous Navigation and Mapping of Snake Robot for Urban Search and Rescue,” In: 2023 International Conference on Robotics and Automation in Industry (ICRAI), Peshawar, Pakistan (2023) pp. 1–8. doi: 10.1109/ICRAI57502.2023.10089544 CrossRefGoogle Scholar
Singh, A., Anshul, C. G. and Choset, H., “Modelling and Path Planning of Snake Robot in Cluttered Environment,” In: 2018 International Conference on Reconfigurable Mechanisms and Robots (ReMAR), Delft, Netherlands (2018) pp. 1–6. doi: 10.1109/REMAR.2018.8449833 CrossRefGoogle Scholar
Li, D., Zhang, Y., Li, P., Law, R., Xiang, Z., Xu, X., Zhu, L. and Wu, E. Q., “Position errors and interference prediction-based trajectory tracking for snake robots,” IEEE/CAA J Automatica Sinica 10(9), 1810–1821 (2023). doi: 10.1109/JAS.2023.123612.CrossRefGoogle Scholar
Cao, Z., Zhang, D. and Zhou, M. C., “Direction control and adaptive path following of 3-D snake-like robot motion,” IEEE Trans Cybernet 52(10), 10980–10987 (2022). doi: 10.1109/TCYB.2021.3055519.CrossRefGoogle ScholarPubMed
Shugen Ma, N. T., Li, B. and Inoue, K., “Analysis of Creeping Locomotion of a Snake Robot on a Slope,” In: 2003 IEEE International Conference on Robotics and Automation (Cat, Taipei, Taiwan (2003) pp. 2073–2078. doi:10.1109/ROBOT.2003.1241899 CrossRefGoogle Scholar