FFRob: An Efficient Heuristic for Task and Motion Planning
Manipulation problemsinvolvingmany objects present substantial challenges for motion planning algorithms due to the high dimensionality and multi-modality of the search space. Symbolic task planners can efficiently construct plans involving many entities but cannot incorporate the constraints from g...
Main Authors: | Garrett, Caelan Reed, Lozano-Perez, Tomas, Kaelbling, Leslie P |
---|---|
Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | en_US |
Published: |
Springer Cham
2017
|
Online Access: | http://hdl.handle.net/1721.1/112348 https://orcid.org/0000-0002-6474-1276 https://orcid.org/0000-0002-8657-2450 https://orcid.org/0000-0001-6054-7145 |
Similar Items
-
FFRob: Leveraging symbolic planning for efficient task and motion planning
by: Garrett, Caelan Reed, et al.
Published: (2022) -
FFRob: Leveraging symbolic planning for efficient task and motion planning
by: Garrett, Caelan Reed, et al.
Published: (2021) -
Sampling-based methods for factored task and motion planning
by: Garrett, Caelan Reed, et al.
Published: (2020) -
Learning to rank for synthesizing planning heuristics
by: Garrett, Caelan Reed, et al.
Published: (2018) -
Sample-Based Methods for Factored Task and Motion Planning
by: Garrett, Caelan, et al.
Published: (2021)