| Asymptotically near-optimal RRT for fast, high-quality motion planning O Salzman, D Halperin IEEE Transactions on Robotics 32 (3), 473-483, 2016 | 248 | 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 | 199 | 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 | 111 | 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 | 69 | 2019 |
| Asymptotically near-optimal motion planning using lower bounds on cost O Salzman, D Halperin arXiv preprint arXiv:1403.7714, 2014 | 60* | 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 | 59 | 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 | 57 | 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 | 52* | 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 | 46 | 2018 |
| Algorithmic motion planning D Halperin, O Salzman, M Sharir Handbook of Discrete and Computational Geometry, 1311-1342, 2017 | 45 | 2017 |
| 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 | 40 | 2019 |
| 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 | 40 | 2014 |
| 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 | 38 | 2020 |
| 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 | 34 | 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 | 34 | 2019 |
| Motion planning via manifold samples O Salzman, M Hemmer, B Raveh, D Halperin Algorithmica 67 (4), 547-565, 2013 | 34 | 2013 |
| 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 | 31 | 2021 |
| Sampling-based robot motion planning O Salzman Communications of the ACM 62 (10), 54-63, 2019 | 31 | 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 | 27 | 2018 |
| POMHDP: Search-based belief space planning using multiple heuristics SK Kim, O Salzman, M Likhachev Proceedings of the International Conference on Automated Planning and …, 2019 | 26 | 2019 |
Dan HalperinProfessor of Computer Science, Tel Aviv UniversityVerified email at tauex.tau.ac.il
