Triangle Sampling Path Planning in Environment with Danger Zones for Assembly/Disassembly

• Autorzy: Peng F. , Zhao Y.

Warianty tytułu

PL

Planowanie drogi w środowisku z zagrożeniami przy próbkowaniu trójkątnym

• Języki publikacji: EN

Abstrakty

EN

To plan a feasible path in the environment with danger zones for assembly/disassembly, a RRT-based path planning algorithm was presented. The algorithm addressed a new density avoided sampling function based on kurtosis coefficient for planning in the free configuration space, and introduced a random sampling function which obtains random state from the triangles that describe the danger zones. The local planner connecting the samples with RRT trees is also introduced. Experimental results show that the algorithm much more effectively searches the paths between danger zones and obstacles.

PL

Zaprezentowano metodę wyznaczania możliwej ścieżki ruchu w środowisku z zagrożeniami. Algorytm bazuje na systemie PRM (probabilistic roadmap) i RRT (rapidly-exploring random trees).

Słowa kluczowe

EN

path planning; random sampling; Rapidly-exploring Random Trees; Configuration Space; Motion Constraints

PL

planowanie drogi; próbkowanie losowe; próbkowanie trójkątne

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 1b
• Strony: 167--172
• Opis fizyczny: Bibliogr. 11 poz., rys., wykr.

Twórcy

autor

Peng F.

autor

Zhao Y.

• School of Naval Architecture & Ocean Engineering, Huazhong University of Science and Technology Wuhan, China,

Bibliografia

• [1] Chang, H. and Li, T.-Y, “Assembly maintainability study with motion planning”, Proceedings of the 1995 IEEE International Conference on Robotics & Automation, pp1012-1017, 1995.
• [2] L. Zhang, X. Huang, Y. Kim and D. Manocha, “D-Plan: Efficient Collision-Free Path Computation for Part Removal and Disassembly”, In Journal of Computer-Aided Design and Applications, vol.15, No.5 pp1209-1212, 2008.
• [3] L. Kavraki, P. Svestka, J. C. Latombe, and M. Overmars, “Probabilistic roadmaps for path planning in highdimensional configuration spaces”, IEEE Trans. Robot. Automat, vol.12, No.4, pp566–580, 1996.
• [4] J. Kuffner and S. LaValle, “RRT-connect: An efficient approach to single-query path planning”, In Proc. IEEE International Conference on Robotics and Automation, vol.35, No.5, pp1806-1812, 2000.
• [5] H.-L. Cheng, D. Hsu, J.-C. Latombe, and G. S´anchez-Ante, “Multi-level free-space dilation for sampling narrow passages in PRM planning”, In Proc. IEEE Int. Conf. on Robotics & Automation, pp1255–1260, 2006.
• [6] S. Redon and M. Lin, “A fast method for local penetration depth computation”, Journal of Graphics Tools, vol.11, No.2, pp37–50, 2006.
• [7] M. Saha, J. Latombe, Y. Chang, Lin, and F. Prinz, “Finding narrow passages withprobabilistic roadmaps: the small step retraction method”, Intelligent Robots and Systems, vol.19, No.3, pp301–319, Dec 2005.
• [8] Danielle. Sent & Mark. H. Overmars, “Motion planning in environments with danger zones”, Proceedings of the 2001 IEEE International Conference on Robotics and Automation, Seoul, Korea, pp1488-1493, 2001.
• [9] LaValle S M, “Rapidly-exploring random trees: a new tool for path planning”, Technical Report TR98-11, Computer Science Dept, Iowa State University, 1998.
• [10] Sohrab Khanmohammadi and Amin Mahdizadeh, “Density avoided sampling: an intelligent sampling technique for Rapidly-exploring Random Trees”, Eighth International Conference on Hybrid Intelligent Systems, pp672-677, 2008.
• [11] LaValle S M. and J. J. Kuffner, “Randomized kinodynamic planning”, International Journal of Robotics Research, vol.20, No.5, pp378–400, May 2001