Assembly Planning from Observations under Physical Constraints

Autor:	Chabal, Thomas, Strudel, Robin, Arlaud, Etienne, Ponce, Jean, Schmid, Cordelia
Rok vydání:	2022
Předmět:	Computer Science - Robotics Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	This paper addresses the problem of copying an unknown assembly of primitives with known shape and appearance using information extracted from a single photograph by an off-the-shelf procedure for object detection and pose estimation. The proposed algorithm uses a simple combination of physical stability constraints, convex optimization and Monte Carlo tree search to plan assemblies as sequences of pick-and-place operations represented by STRIPS operators. It is efficient and, most importantly, robust to the errors in object detection and pose estimation unavoidable in any real robotic system. The proposed approach is demonstrated with thorough experiments on a UR5 manipulator. Comment: IROS 2022. See the project webpage at https://www.di.ens.fr/willow/research/assembly-planning/
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2204.09616 Zobrazit plný text záznamu View this record from Arxiv