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Locomotion Planning for Quadruped Robot Walking on Lunar Rough Terrain

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Abstract

This paper focuses on the locomotion planning for a quadruped robot walking on the lunar rough terrain. Firstly, the detailed terrain data of the explorable area acquired by the navigation camera is filtered. The terrain is afterwards triangular meshed and reconstructed as a simplified triangular grid model with terrain features retained. Then, the reinforcement learning method is used to plan the path of the robot in the grid-based environment. It employs terrain relief and roughness as the rewards, therefore intelligently determining the optimal detection route with maximum cumulative reward. Finally, gait planning is carried out to make the legs actuate adaptively to the path. Particularly, the step sequence is adjusted with different steering angles, and the footsteps are decided based on the robot mechanism constraints and uneven terrain conditions. Numerical simulations illustrate the walking process of the quadruped robot. The results show that the robot can learn the optimal path with fewer trunk undulations, and generate continuous, stable, and safe gaits. It proves that the locomotion planning method can effectively improve the mobile stability, efficiency, and adaptability of the quadruped robot when walking on the lunar surface.

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References

  1. Stooke PJ (2017) Luna missions

  2. Miller FP, Vandome AF, McBrewster J et al (2011) Moon landing. Alphascript Publishing

  3. Wang Q, Liu J (2016) A Chang’e-4 mission concept and vision of future Chinese lunar exploration activities. Acta Astronaut 127:678–683

    Article  Google Scholar 

  4. Lopez-Arreguin AJR, Montenegro S (2020) Improving limitations of rover missions in the moon and planets by unifying vehicle–terrain interaction models. Adv Astronaut Sci Technol 3:17–28

    Article  Google Scholar 

  5. Wooden DT (2006) Graph-based path planning for mobile robots. Georgia Institute of Technology

  6. Panov S, Koceska N (2014) Global path planning in grid-based environments using novel metaheuristic algorithm. In: 5th ICT Innovations Conference. Springer International Publishing

  7. Li Z, Ding L, You B et al (2019) A local dynamic path planning approach for WMRs based on fuzzy dual CHOMP. In: 2019 IEEE 9th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER). IEEE

  8. [[8] Liu JJ, Ren X, Mu LL et al (2014) Digital terrain model reconstruction and preliminary scientific exploration planning of the Chang'E 3. In: ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-4(4), 149–151

  9. Belter D, Piotr S (2011) Rough terrain map** and classification for foothold selection in a walking robot. J Field Robot 28(4):497–528

    Article  Google Scholar 

  10. Ajallooeian M, Gay S, Tuleu A et al (2013) Modular control of limit cycle locomotion over unperceived rough terrain. In: IEEE/RSJ International Conference on Intelligent Robots & Systems. IEEE

  11. Rebula JR, Neuhaus PD, Bonnlander BV et al (2007) A controller for the LittleDog quadruped walking on rough terrain. In: IEEE International Conference on Robotics & Automation. IEEE

  12. Erden MS (2011) Optimal protraction of a biologically inspired robot leg. J Intell Rob Syst 64(3–4):301–322

    Article  Google Scholar 

  13. Kolter JZ, Ng AY (2009) Task-space trajectories via cubic spline optimization. Robotics and Automation, 2009. ICRA '09. In: IEEE International Conference on. IEEE

  14. Chu XY, Hu Q, Zhang JR (2018) Path planning and collision avoidance for a multi-arm space maneuverable robot. IEEE Trans Aerosp Electron Syst 54(1):217–232

    Article  Google Scholar 

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Acknowledgements

Funded by Science and Technology on Space Intelligent Control Laboratory, China, No. HTKJ2021KL502001.

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Authors and Affiliations

  1. Bei**g Institute of Control Engineering (BICE), China Academy of Space Technology (CAST), Bei**g, 100091, China

    **aoyu Chu, Qiang Zhang, Yuanzi Zhou, Wen Wen, **aohui Li & Weihui Liu

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  1. **aoyu Chu
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  2. Qiang Zhang
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  3. Yuanzi Zhou
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  4. Wen Wen
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  5. **aohui Li
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  6. Weihui Liu
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Correspondence to **aoyu Chu.

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Chu, X., Zhang, Q., Zhou, Y. et al. Locomotion Planning for Quadruped Robot Walking on Lunar Rough Terrain. Adv. Astronaut. Sci. Technol. 5, 93–102 (2022). https://doi.org/10.1007/s42423-022-00104-w

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  • DOI: https://doi.org/10.1007/s42423-022-00104-w

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