LTA*: Local tangent based A* for optimal path planning
Author:
Funder
Higher Education Commision, Pakistan
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
http://link.springer.com/content/pdf/10.1007/s10514-020-09956-3.pdf
Reference41 articles.
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3. Arslan, O., & Tsiotras, P. (2013). Use of relaxation methods in sampling-based algorithms for optimal motion planning. In 2013 IEEE International Conference on Robotics and Automation (ICRA) (pp. 2421–2428). IEEE.
4. Chazelle, B. (1984). Convex partitions of polyhedra: A lower bound and worst-case optimal algorithm. SIAM Journal on Computing, 13(3), 488–507.
5. Chazelle, B., & Dobkin, D. P. (1985). Optimal convex decompositions. In Machine Intelligence and pattern recognition (Vol. 2, pp. 63–133). Elsevier.
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