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Compositional Diffusion-Based Continuous Constraint Solvers
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2026-02-20 15:17:28
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Diffusion-CCSP Compositional Diffusion-Based Continuous Constraint Solvers CoRL 2023 Zhutian Yang 1 , Jiayuan Mao 1 , Yilun Du 1 , Jiajun Wu 2 , Joshua B. Tenenbaum 1 , Tomás Lozano-Pérez 1 , Leslie Kaelbling 1 1 MIT, 2 Stanford Paper Code Diffusion-CCSP is an approach for learning to solve continuous constraint satisfaction problems in robotic reasoning and planning, for example, packing objects without collisions. Example Training Data Placement Poses Generated by Diffusion-CCSP Execution Trajectories Planning by RRT Motivations Continuous Constraint Satisfaction Problems require robot planner to conform to multiple geometric, physical, and qualitative constraints simultaneously. For example, to place A into the tray in the figure below, we need to generate the grasping pose grasp A, placement pose pose A, and the robot arm trajectory. Our Diffusion-CCSP derives global solutions to CCSPs by representing them as fact...
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