| Informed RRT*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic JD Gammell, SS Srinivasa, TD Barfoot 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2014 | 920 | 2014 |
| Batch Informed Trees (BIT*): Sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs JD Gammell, SS Srinivasa, TD Barfoot 2015 IEEE International Conference on Robotics and Automation (ICRA), 2015 | 502 | 2015 |
| Informed sampling for asymptotically optimal path planning JD Gammell, TD Barfoot, SS Srinivasa IEEE Transactions on Robotics 34 (4), 966-984, 2018 | 135 | 2018 |
| Regionally Accelerated Batch Informed Trees (RABIT*): A framework to integrate local information into optimal path planning S Choudhury, JD Gammell, TD Barfoot, SS Srinivasa, S Scherer 2016 IEEE International Conference on Robotics and Automation (ICRA), 4207-4214, 2016 | 102 | 2016 |
| Batch Informed Trees (BIT*): Informed asymptotically optimal anytime search JD Gammell, TD Barfoot, SS Srinivasa The International Journal of Robotics Research 39 (5), 543-567, 2020 | 101 | 2020 |
| Adaptively Informed Trees (AIT*): Fast Asymptotically Optimal Path Planning through Adaptive Heuristics MP Strub, JD Gammell 2020 IEEE International Conference on Robotics and Automation (ICRA), 3191-3198, 2020 | 65 | 2020 |
| Asymptotically Optimal Sampling-Based Motion Planning Methods JD Gammell, MP Strub Annual Review of Control, Robotics, and Autonomous Systems 4 (1), 295-318, 2021 | 57 | 2021 |
| Advanced BIT* (ABIT*): Sampling-Based Planning with Advanced Graph-Search Techniques MP Strub, JD Gammell 2020 IEEE International Conference on Robotics and Automation (ICRA), 130-136, 2020 | 49 | 2020 |
| Multimotion Visual Odometry (MVO): Simultaneous estimation of camera and third-party motions KM Judd, JD Gammell, P Newman 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 43 | 2018 |
| Into darkness: Visual navigation based on a lidar-intensity-image pipeline TD Barfoot, C McManus, S Anderson, H Dong, E Beerepoot, CH Tong, ... Robotics Research: The 16th International Symposium ISRR, 487-504, 2016 | 37 | 2016 |
| Surface Edge Explorer (SEE): Planning next best views directly from 3D observations R Border, JD Gammell, P Newman 2018 IEEE International Conference on Robotics and Automation (ICRA), 1-8, 2018 | 31 | 2018 |
| The Oxford multimotion dataset: Multiple SE(3) motions with ground truth KM Judd, JD Gammell IEEE Robotics and Automation Letters 4 (2), 800-807, 2019 | 27 | 2019 |
| Adaptively Informed Trees (AIT*) and Effort Informed Trees (EIT*): Asymmetric bidirectional sampling-based path planning MP Strub, JD Gammell The International Journal of Robotics Research 41 (4), 390-417, 2022 | 22 | 2022 |
| A Mission Control Architecture for robotic lunar sample return as field tested in an analogue deployment to the sudbury impact structure JE Moores, R Francis, M Mader, GR Osinski, T Barfoot, N Barry, G Basic, ... Advances in space research 50 (12), 1666-1686, 2012 | 19 | 2012 |
| Rover odometry aided by a star tracker JD Gammell, CH Tong, P Berczi, S Anderson, TD Barfoot, J Enright 2013 IEEE Aerospace Conference, 1-10, 2013 | 16 | 2013 |
| Navigation on the line: traversability analysis and path planning for extreme-terrain rappelling rovers M Paton, M Strub, T Brown, R Greene, J Lizewski, V Patel, J Gammell, ... IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020 | 12 | 2020 |
| Informed anytime search for continuous planning problems JD Gammell University of Toronto, 2017 | 12 | 2017 |
| 3D surface mapping using a semiautonomous rover: A planetary analog field experiment RS Merali, C Tong, J Gammell, J Bakambu, E Dupuis, TD Barfoot Proc. of the 2012 Int. Symposium on Artificial Intelligence, Robotics and …, 2012 | 12 | 2012 |
| Manufacturable MEMS MiniSEMs R Saini, Z Jandric, J Gammell, SAM Mentink, D Tuggle Microelectronic engineering 83 (4-9), 1376-1381, 2006 | 12 | 2006 |
| Proactive estimation of occlusions and scene coverage for planning next best views in an unstructured representation R Border, J Gammell IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020 | 11 | 2020 |
Timothy D BarfootProfessor, University of TorontoVerified email at utoronto.ca
