Scalable Learned Geometric Feasibility for Cooperative Grasp and Motion Planning

This letter proposes a novel learned feasibility estimator that considers multi-modal grasp poses for grasp and motion planning. Grasp poses inherently have multi-modal structures, that is, continuous and discrete parameters. Mixed-integer programming (MIP) is one method that solves these multi-moda...

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Veröffentlicht in:	IEEE robotics and automation letters 2022-10, Vol.7 (4), p.11545-11552
Hauptverfasser:	Park, Suhan, Kim, Hyoung Cheol, Baek, Jiyeong, Park, Jaeheung
Format:	Artikel
Sprache:	eng
Schlagworte:	Costs Deep learning in grasping and manipulation Feasibility Grasping Grippers Integer programming Linear programming manipulation planning Mixed integer Motion planning Multiple robots Object oriented modeling Parameters Planning Robots Task analysis
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