Advertisement

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

  • Yingjie Qian
  • Jianjun YuanEmail author
  • Weiwei Wan
Article
  • 23 Downloads

Abstract

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.

Keywords

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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Compliance with Ethical Standards

Conflict of interests

The authors declare that they have no conflict of interest.

Supplementary material

10846_2019_1113_MOESM1_ESM.mp4 (17.5 mb)
(MP4 17.5 MB)
10846_2019_1113_MOESM2_ESM.mp4 (1.8 mb)
(MP4 1.80 MB)

References

  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)CrossRefGoogle 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)CrossRefGoogle 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)Google Scholar
  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)Google Scholar
  7. 7.
    Tomasz, R.: Obstacle avoidance in space robotics: Review of major challenges and proposed solution. Prog. Aerosp. Sci. 101, 31–48 (2018)CrossRefGoogle 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)CrossRefGoogle 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)Google Scholar
  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)Google Scholar
  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). numbersCrossRefGoogle 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)Google Scholar
  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)Google Scholar
  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)CrossRefGoogle Scholar
  16. 16.
    Dijkstra, E.W.: A Note on Two Problems in Connexion with Graphs. Springer, New York (1959)CrossRefGoogle 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)CrossRefGoogle 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)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Uras, T., Koenig, S.: An empirical comparison of any-angle path-planning algorithms. Eighth Annual Symposium on Combinatorial Search (2015)Google Scholar
  20. 20.
    Ferguson, D., Stentz, A.: Using interpolation to improve path planning: The Field D* algorithm. J. Field Robot. 23(2), 79–101 (2006)CrossRefGoogle 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)Google Scholar
  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)MathSciNetCrossRefGoogle 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)Google Scholar
  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)Google Scholar
  25. 25.
    Botea, A., Mueller, M., Schaeer, J.: Near optimal hierarchical path-finding. Journal of Game Development 1(1), 7–28 (2004)Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Robotics InstituteShanghai Jiaotong UniversityShanghaiPeople’s Republic of China
  2. 2.Shanghai Robotics InstituteShanghai UniversityShanghaiPeople’s Republic of China
  3. 3.School of Engineering ScienceOsaka UniversityOsakaJapan

Personalised recommendations