Articles with public access mandates - Luke ShimanukiLearn more
Available somewhere: 5
Learning value functions with relational state representations for guiding task-and-motion planning
B Kim, L Shimanuki
Conference on robot learning, 955-968, 2020
Mandates: US National Science Foundation, US Department of Defense
Representation, learning, and planning algorithms for geometric task and motion planning
B Kim, L Shimanuki, LP Kaelbling, T Lozano-Pérez
The International Journal of Robotics Research 41 (2), 210-231, 2022
Mandates: US National Science Foundation, US Department of Defense
Hardness of 3d motion planning under obstacle uncertainty
L Shimanuki, B Axelrod
International Workshop on the Algorithmic Foundations of Robotics, 852-867, 2018
Mandates: US National Science Foundation, US Department of Defense
Hardness of motion planning with obstacle uncertainty in two dimensions
L Shimanuki, B Axelrod
The International Journal of Robotics Research 40 (10-11), 1151-1166, 2021
Mandates: US National Science Foundation, US Department of Defense
Efficient Motion Planning Under Obstacle Uncertainty with Local Dependencies
B Axelrod, L Shimanuki
International Workshop on the Algorithmic Foundations of Robotics, 68-84, 2022
Mandates: US National Science Foundation, US Department of Defense
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