Oren Salzman
Cited by
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Asymptotically near-optimal RRT for fast, high-quality motion planning
O Salzman, D Halperin
IEEE Transactions on Robotics 32 (3), 473-483, 2016
Finding a needle in an exponential haystack: Discrete RRT for exploration of implicit roadmaps in multi-robot motion planning
K Solovey, O Salzman, D Halperin
The International Journal of Robotics Research 35 (5), 501-513, 2016
Research challenges and opportunities in multi-agent path finding and multi-agent pickup and delivery problems
O Salzman, R Stern
Proceedings of the 19th International Conference on Autonomous Agents and …, 2020
Generalized lazy search for robot motion planning: Interleaving search and edge evaluation via event-based toggles
A Mandalika, S Choudhury, O Salzman, S Srinivasa
Proceedings of the International Conference on Automated Planning and …, 2019
Asymptotically near-optimal motion planning using lower bounds on cost
O Salzman, D Halperin
arXiv preprint arXiv:1403.7714, 2014
The provable virtue of laziness in motion planning
N Haghtalab, S Mackenzie, A Procaccia, O Salzman, S Srinivasa
Proceedings of the International Conference on Automated Planning and …, 2018
Lazy receding horizon A* for efficient path planning in graphs with expensive-to-evaluate edges
A Mandalika, O Salzman, S Srinivasa
Proceedings of the international conference on automated planning and …, 2018
Sparsification of motion-planning roadmaps by edge contraction
D Shaharabani, O Salzman, PK Agarwal, D Halperin
2013 IEEE International Conference on Robotics and Automation, 4098-4105, 2013
New perspective on sampling-based motion planning via random geometric graphs
K Solovey, O Salzman, D Halperin
The International Journal of Robotics Research 37 (10), 1117-1133, 2018
Algorithmic motion planning
D Halperin, O Salzman, M Sharir
Handbook of Discrete and Computational Geometry, 1311-1342, 2017
On the power of manifold samples in exploring configuration spaces and the dimensionality of narrow passages
O Salzman, M Hemmer, D Halperin
IEEE Transactions on Automation Science and Engineering 12 (2), 529-538, 2014
Toward asymptotically-optimal inspection planning via efficient near-optimal graph search
M Fu, A Kuntz, O Salzman, R Alterovitz
Robotics science and systems: online proceedings 2019, 2019
Collision detection or nearest-neighbor search? On the computational bottleneck in sampling-based motion planning
M Kleinbort, O Salzman, D Halperin
Algorithmic Foundations of Robotics XII: Proceedings of the Twelfth Workshop …, 2020
Motion planning via manifold samples
O Salzman, M Hemmer, B Raveh, D Halperin
Algorithmica 67 (4), 547-565, 2013
Provably constant-time planning and replanning for real-time grasping objects off a conveyor belt
F Islam, O Salzman, A Agarwal, M Likhachev
The International journal of robotics research 40 (12-14), 1370-1384, 2021
Minimizing task-space Frechet error via efficient incremental graph search
R Holladay, O Salzman, S Srinivasa
IEEE Robotics and Automation Letters 4 (2), 1999-2006, 2019
Cooperative multi-agent path finding: Beyond path planning and collision avoidance
N Greshler, O Gordon, O Salzman, N Shimkin
2021 International symposium on multi-robot and multi-agent systems (MRS), 20-28, 2021
Sampling-based robot motion planning
O Salzman
Communications of the ACM 62 (10), 54-63, 2019
An efficient algorithm for computing high-quality paths amid polygonal obstacles
PK Agarwal, K Fox, O Salzman
ACM Transactions on Algorithms (TALG) 14 (4), 1-21, 2018
Generalizing informed sampling for asymptotically-optimal sampling-based kinodynamic planning via markov chain monte carlo
D Yi, R Thakker, C Gulino, O Salzman, S Srinivasa
2018 IEEE International Conference on Robotics and Automation (ICRA), 7063-7070, 2018
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