Sept. 10, 2023, 5:51 a.m. | Dhanshree Shripad Shenwai


The capacity to choose continuous values, such as grasps and object placements, that satisfy complicated geometric and physical constraints, like stability and lack of collision, is crucial for robotic manipulation planning. Samplers for each type of constraint have traditionally been learned or optimized separately in existing methods. However, a general-purpose solver is needed for complex […]

The post How Can Robots Make Better Decisions? MIT and Stanford Researchers Introduce Diffusion-CCSP for Advanced Robotic Reasoning and Planning appeared first on MarkTechPost …

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