Abstract
To prolong the service life of satellites, space crawling robots are used for in-orbit services such as inspection and repair. However, the complex structure of the satellite surface requires path planning. Most current path planning algorithms are only applicable to the planar and 3D unconstrained case, and cannot be applied to CubeSat surface with abrupt changes in normal vectors. In this paper, we design a cube unfolding method to reduce the cube surface path planning problem to a planar path planning problem. This is accomplished by obtaining obstacle point cloud data through laser radar and converting the point cloud data into a grid map using the Gmapping algorithm. And considering the limitation of arithmetic power for operations on satellites, this paper uses PSO to solve this planar path planning problem. The experimental results show that the method can be applied to the surface of the CubeSat.
Similar content being viewed by others
Availability of Data and Materials
The data underlying this article will be shared on reasonable request to the corresponding author.
References
Liu Y, She H, Meng B, Huang J A (2023) Method of surrounding escapable space target by combining game with optimization. In: 2023 42nd Chinese control conference (CCC), pp 8088–8093. IEEE
Shih C-L (1999) Ascending and descending stairs for a biped robot. IEEE Trans Syst Man Cybern A Syst Hum 29(3):255–268
Siekmann J, Green K, Warila J, Fern A, Hurst J (2021) Blind bipedal stair traversal via sim-to-real reinforcement learning. arXiv preprint arXiv:2105.08328
Lo C-C (1999) Efficient cutter-path planning for five-axis surface machining with a flat-end cutter. Comput-Aided Des 31(9):557–566
Jiang J, Ma Y (2020) Path planning strategies to optimize accuracy, quality, build time and material use in additive manufacturing: a review. Micromachines 11(7):633
Contreras-Cruz MA, Ayala-Ramirez V, Hernandez-Belmonte UH (2015) Mobile robot path planning using artificial bee colony and evolutionary programming. Appl Soft Comput 30:319–328
Murphy K, Russell S (2001) In: Doucet A, Freitas N, Gordon N (eds) Rao-Blackwellised particle filtering for dynamic Bayesian networks. Springer, New York, pp 499–515. https://doi.org/10.1007/978-1-4757-3437-9_24
Grisetti G, Stachniss C, Burgard W (2007) Improved techniques for grid mapping with Rao-Blackwellized particle filters. IEEE Trans Robot 23(1):34–46
Warren CW (1989) Global path planning using artificial potential fields. In: 1989 IEEE international conference on robotics and automation. IEEE Computer Society, pp 316–317
Zhang jian-ying, L.d. Zhao zhi-ping (2006) A path planning method for mobile based on artificial potential field. J Harb Inst Technol (1306–1309)
Duchoň F, Babinec A, Kajan M, Beňo P, Florek M, Fico T, Jurišica L (2014) Path planning with modified a star algorithm for a mobile robot. Procedia Eng 96:59–69
Sun Y, Fang M, Su Y (2021) AGV path planning based on improved Dijkstra algorithm. J Phys Conf Ser 1746:012052
Wang X, Liu Z, Liu J (2023) Mobile robot path planning based on an improved A* algorithm. In: International conference on computer graphics, artificial intelligence, and data processing (ICCAID 2022), vol 12604. SPIE, pp 1093–1098
Luo M, Hou X, Yang J (2020) Surface optimal path planning using an extended Dijkstra algorithm. IEEE Access 8:147827–147838
Ting Y, Lei WI, Jar HC (2002) A path planning algorithm for industrial robots. Comput Ind Eng 42(2):299–308. https://doi.org/10.1016/S0360-8352(02)00013-X
Yang G, Hu C, Meng H, Wang SY (2019) Constraint path planning for an autonomous wall spray coating robot. In: 2019 IEEE international conference on robotics and biomimetics (ROBIO). IEEE, pp 2977–2983
Zhang M, Xin S, Fan H (2023) Path planning for mobile robot based on improved genetic algorithm. In: 2023 4th International conference on mechatronics technology and intelligent manufacturing (ICMTIM). IEEE, pp 382–386
Song B, Wang Z, Zou L (2021) An improved PSO algorithm for smooth path planning of mobile robots using continuous high-degree Bezier curve. Appl Soft Comput 100:106960
Ge X, Bian F (2007) On algorithm for 3d surface route optimization based on ant colony optimization. Geomat Inf Sci Wuhan Univ 32(4):366–368
Chen W, Zhang W, Hu S, Shen X (2021) An indoor mobile robot mapping and navigation method integrating depth camera and lidar. Intell Comput Appl 11(04):159–163
Funding
No funding was received.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
No competing interest.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Yihan, C., Mingtao, C., Wei, L. et al. Crawling Robot Path Planning on the Surface of the CubeSat. Adv. Astronaut. Sci. Technol. (2024). https://doi.org/10.1007/s42423-024-00149-z
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s42423-024-00149-z