Improved Trajectory Planning Method for Space Robot-System with Collision Prediction


This paper studies the trajectory planning problem for space robot system including two 7 degrees-of-freedom (DOFs) space manipulators. The base disturbance problem is not discussed. An intuitive close-form inverse-kinematic solution is first deduced to convert the Cartesian pose of end-effector into joint configurations. Two innovative functions, crawling function and cascade connection between Core Module Manipulator (CMM) and Experimental Module Manipulator (EMM) are studied and provided with mathematical solutions. Their purposes are to broaden the workspace while requiring higher demands on the planning method. Collision prediction including collision against the environment and against the robot itself is then analyzed to eliminate the tunneling problem and enhance efficiency. Finally, an improved trajectory planning method based on Lazy Theta* which is an algorithm of any-angle-path planning is proposed and adjusted to different planning conditions. Simulation results prove the comprehensive validity of this method. The collision-free trajectory is reasonable and optimized for shorter length and less turns. This method has preferable efficiency and utility to complex environment and changing free configuration space.

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  1. 1.

    Xu, W., Liang, B., Xu, Y.: Survey of modeling, planning and ground verication of space robotic systems. Acta Astronaut. 68(11), 1629–1649 (2011)

    Article  Google Scholar 

  2. 2.

    Flores-Abad, A., Ou, M., Pham, K., Ulrich, S.: A review of space robotics technologies for on-orbit servicing. Prog. Aerosp. Sci. 68(8), 1–26 (2014)

    Article  Google Scholar 

  3. 3.

    Hong, L., Nannan, J., Yechao, L.: Review of space manipulator technology. Manned Spaceflight 21(5), 435–443 (2015)

    Google Scholar 

  4. 4.

    Li, J., Huo, X., Liu, Y., Hong, L.: An integrated inverse kinematic approach for the 7-DOF humanoid arm with offset wrist. In: IEEE International Conference on Robotics & Biomimetics (2013)

  5. 5.

    Daming, L.I., Rao, W., Chengwei, H.U., Wang, Y., Tang, Z., Wang, Y.: Key technology review of the research on the space station manipulator. Manned Spaceflight 3, 238–242 (2014)

    Google Scholar 

  6. 6.

    Chu, X., Quan, H., Zhang, J.: Path planning and collision avoidance for a Multi-Arm space maneuverable robot. IEEE Transactions on Aerospace & Electronic Systems (2017)

  7. 7.

    Tomasz, R.: Obstacle avoidance in space robotics: Review of major challenges and proposed solution. Prog. Aerosp. Sci. 101, 31–48 (2018)

    Article  Google Scholar 

  8. 8.

    Luo, J., Yu, M., Wang, M., Yuan, J.: A fast trajectory planning framework with task-priority for space robot. Acta Astronaut. 152, 823–835 (2018)

    Article  Google Scholar 

  9. 9.

    Jing, X., Jiang, Z., Hong, L., Cai, H., Wu, G.: A manipulator’s safety control strategy based on fast continuous collision detection. In: IEEE International Conference on Robotics & Biomimetics (2013)

  10. 10.

    Zheng, H., Yun, L., Hao, W., Dongping, J.: Ground-based experiment of capturing space debris based on artificial potential field, vol. 152. numbers (2018)

  11. 11.

    Cheng, Z.A., Hou, X., Zhang, X., Lu, Z., Guo, J., Song, C.: In-orbit assembly mission for the Space Solar Power Station. Acta Astronaut. 129, 299–308 (2016). numbers

    Article  Google Scholar 

  12. 12.

    Rybus, T., Seweryn, K.: Application of Rapidly-exploring Random Trees (RRT) algorithm for trajectory planning of free-floating space manipulator. International Workshop on Robot Motion & Control (2015)

  13. 13.

    Benevides, J.R., Grassi, V.: Autonomous path planning of free-floating manipulators using RRT-based algorithms. In: 2015 12th Latin American Robotics Symposium and 2015 3rd Brazilian Symposium on Robotics (LARS-SBR) (2015)

  14. 14.

    Chen, Z., Zhou, W.: Path planning for a space-based manipulator system based on quantum genetic algorithm. J. Robot. 2017, 1–10 (2017)

    Google Scholar 

  15. 15.

    Wang, M., Luo, J., Walter, U.: Trajectory planning of free-floating space robot using Particle Swarm Optimization (PSO). Acta Astronaut. 112, 77–88 (2015)

    Article  Google Scholar 

  16. 16.

    Dijkstra, E.W.: A Note on Two Problems in Connexion with Graphs. Springer, New York (1959)

    Book  Google Scholar 

  17. 17.

    Gao, X., Jia, Q., Sun, H., Chen, G.: Research on path planning for 7-DOF space manipulator to avoid obstacle based on a* algorithm. Sens. Lett. 9(4), 1515–1519 (2011)

    Article  Google Scholar 

  18. 18.

    Bhargava, T.V., Issac, K.K.: Minimum time Collision-Free trajectories for grabbing a Non-Tumbling satellite. IFAC-PapersOnLine 49(1), 142–147 (2016)

    MathSciNet  Article  Google Scholar 

  19. 19.

    Uras, T., Koenig, S.: An empirical comparison of any-angle path-planning algorithms. Eighth Annual Symposium on Combinatorial Search (2015)

  20. 20.

    Ferguson, D., Stentz, A.: Using interpolation to improve path planning: The Field D* algorithm. J. Field Robot. 23(2), 79–101 (2006)

    Article  Google Scholar 

  21. 21.

    Carsten, J., Ferguson, D., Stentz, A.: 3D field d*: Improved path planning and replanning in three dimensions. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (2006)

  22. 22.

    Daniel, K., Nash, A., Koenig, S., Felner, A.: Theta*: Any-angle path planning on grids. J. Artif. Intell. Res. 39, 533–579 (2010)

    MathSciNet  Article  Google Scholar 

  23. 23.

    Nash, A., Koenig, S., Tovey, C.: Lazy Theta*: Any-angle path planning and path length analysis in 3D. In: Twenty-Fourth AAAI Conference on Artificial Intelligence (2010)

  24. 24.

    Yap, P., Burch, N., Holte, R., Schaeffer, J.: Block A*: Database-driven search with applications in any-angle path-planning 2011. In: Proceedings of the AAAI Conference on Artificial Intelligence (2011)

  25. 25.

    Botea, A., Mueller, M., Schaeer, J.: Near optimal hierarchical path-finding. Journal of Game Development 1(1), 7–28 (2004)

    Google Scholar 

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Correspondence to Jianjun Yuan.

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Qian, Y., Yuan, J. & Wan, W. Improved Trajectory Planning Method for Space Robot-System with Collision Prediction. J Intell Robot Syst 99, 289–302 (2020).

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  • 7DOF space robot-system
  • Collision prediction
  • Trajectory planning
  • Robot crawling
  • Cascade connection