Articles with public access mandates - Leslie KaelblingLearn more
Not available anywhere: 1
Long-horizon manipulation of unknown objects via task and motion planning with estimated affordances
A Curtis, X Fang, LP Kaelbling, T Lozano-Pérez, CR Garrett
2022 International Conference on Robotics and Automation (ICRA), 1940-1946, 2022
Mandates: US National Science Foundation, US Department of Defense
Available somewhere: 70
Generalization in deep learning
K Kawaguchi, LP Kaelbling, Y Bengio
arXiv preprint arXiv:1710.05468 1 (8), 2017
Mandates: US National Science Foundation, US Department of Defense, Natural Sciences …
Integrated task and motion planning
CR Garrett, R Chitnis, R Holladay, B Kim, T Silver, LP Kaelbling, ...
Annual review of control, robotics, and autonomous systems 4 (1), 265-293, 2021
Mandates: US National Science Foundation, US Department of Defense
From skills to symbols: Learning symbolic representations for abstract high-level planning
G Konidaris, LP Kaelbling, T Lozano-Perez
Journal of Artificial Intelligence Research 61, 215-289, 2018
Mandates: US Department of Defense
Pddlstream: Integrating symbolic planners and blackbox samplers via optimistic adaptive planning
CR Garrett, T Lozano-Pérez, LP Kaelbling
Proceedings of the international conference on automated planning and …, 2020
Mandates: US National Science Foundation, US Department of Defense
A constraint-based method for solving sequential manipulation planning problems
T Lozano-Pérez, LP Kaelbling
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2014
Mandates: National Research Foundation, Singapore
Ffrob: Leveraging symbolic planning for efficient task and motion planning
CR Garrett, T Lozano-Perez, LP Kaelbling
The International Journal of Robotics Research 37 (1), 104-136, 2018
Mandates: US National Science Foundation, US Department of Defense
Ffrob: An efficient heuristic for task and motion planning
CR Garrett, T Lozano-Pérez, LP Kaelbling
Algorithmic Foundations of Robotics XI: Selected Contributions of the …, 2015
Mandates: National Research Foundation, Singapore
Modeling and planning with macro-actions in decentralized POMDPs
C Amato, G Konidaris, LP Kaelbling, JP How
Journal of Artificial Intelligence Research 64, 817-859, 2019
Mandates: US National Science Foundation, US Department of Defense, US National …
Modular meta-learning
F Alet, T Lozano-Pérez, LP Kaelbling
Conference on robot learning, 856-868, 2018
Mandates: US National Science Foundation, US Department of Defense, Banking Foundation …
Augmenting physical simulators with stochastic neural networks: Case study of planar pushing and bouncing
A Ajay, J Wu, N Fazeli, M Bauza, LP Kaelbling, JB Tenenbaum, ...
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
Mandates: US National Science Foundation, US Department of Defense
Online replanning in belief space for partially observable task and motion problems
CR Garrett, C Paxton, T Lozano-Pérez, LP Kaelbling, D Fox
2020 IEEE International Conference on Robotics and Automation (ICRA), 5678-5684, 2020
Mandates: US National Science Foundation, US Department of Defense
Learning compositional models of robot skills for task and motion planning
Z Wang, CR Garrett, LP Kaelbling, T Lozano-Pérez
The International Journal of Robotics Research 40 (6-7), 866-894, 2021
Mandates: US National Science Foundation, US Department of Defense
Graph element networks: adaptive, structured computation and memory
F Alet, AK Jeewajee, MB Villalonga, A Rodriguez, T Lozano-Perez, ...
International Conference on Machine Learning, 212-222, 2019
Mandates: US National Science Foundation, US Department of Defense
Learning to guide task and motion planning using score-space representation
B Kim, Z Wang, LP Kaelbling, T Lozano-Pérez
The International Journal of Robotics Research 38 (7), 793-812, 2019
Mandates: US National Science Foundation, US Department of Defense
Policy search for multi-robot coordination under uncertainty
C Amato, G Konidaris, A Anders, G Cruz, JP How, LP Kaelbling
The International Journal of Robotics Research 35 (14), 1760-1778, 2016
Mandates: US National Science Foundation
Sampling-based methods for factored task and motion planning
CR Garrett, T Lozano-Pérez, LP Kaelbling
The International Journal of Robotics Research 37 (13-14), 1796-1825, 2018
Mandates: US National Science Foundation, US Department of Defense
PDDL planning with pretrained large language models
T Silver, V Hariprasad, RS Shuttleworth, N Kumar, T Lozano-Pérez, ...
NeurIPS 2022 foundation models for decision making workshop, 2022
Mandates: US National Science Foundation, US Department of Defense
Planning with learned object importance in large problem instances using graph neural networks
T Silver, R Chitnis, A Curtis, JB Tenenbaum, T Lozano-Pérez, ...
Proceedings of the AAAI conference on artificial intelligence 35 (13), 11962 …, 2021
Mandates: US National Science Foundation, US Department of Defense
Active model learning and diverse action sampling for task and motion planning
Z Wang, CR Garrett, LP Kaelbling, T Lozano-Pérez
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
Mandates: US National Science Foundation, US Department of Defense
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