showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably ...
Motion planning optimal path planning sampling-based algorithms random geometric graphs 摘要 During the last decade, sampling-based path planning algorithms, such as probabilistic roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well in practice and possess theoretical...
Alternatively, by leverag-ing structure in specif ic problem formulations or computational methods designed for exhaustivity(e.g., branch and bound), a large range of algorithms with deterministic accuracy and performancearXiv:2112.05745v3 [eess.SY] 13 Apr 2022 ...
one of the primary objective of this work is to generalize PRM/RRT to solve motion planning with uncertainty.We first present generalizations of randomized sampling based algorithms PRM and RRT, to incorporate the process uncertainty, and... Kumar,Sandip 被引量: 25发表: 2011年 Computationally Effi...
During the last decade, sampling-based path planning algorithms, such as probabilistic roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well in practice and possess ...关键词: Motion planning optimal path planning random geometric graphs sampling-based alg...
16.410/413PrinciplesofAutonomyandDecisionMakingLecture15:Sampling-BasedAlgorithmsforMotionPlanningEmilioFrazzoliAeronauticsandAstronauticsM..
Submodular Approximation: Sampling-based Algorithms and Lower Bounds We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions.The new problems include submodular load balancing,... Z Svitkina,L Fleischer - Sy...
FLEISCHER, Submodular approximation: Sampling-based algorithms and lower bounds, SIAM Journal on Computing, 40 (2011), pp. 1715-1737.Z. Svitkina and L. Fleischer. Submodular approximation: Sampling-based algorithms and lower bounds. SIAM Journal of Computing, 40(6):1715-1737, 2011....
By exploiting the artificial sequential structure of the existing simple BLAST detection method based on ing and cancellation, the proposed algorithms achieve an error probability performance that is orders of magnitude better than the traditional BLAST detection schemes while maintaining a low computational...
During the last decade, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs) have been shown to work well in practice and to possess theoretical guarantees such as probabilistic completeness. However, no theoretical bounds on the quality of the solu...