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Found 4 papers, 3 papers with code
Dynamics-Guided Diffusion Model for Robot Manipulator Design
The design objective constructed from the target and predicted interaction profiles provides a gradient to guide the refinement of finger geometry for the task.
Semantic Abstraction: Open-World 3D Scene Understanding from 2D Vision-Language Models
We study open-world 3D scene understanding, a family of tasks that require agents to reason about their 3D environment with an open-set vocabulary and out-of-domain visual inputs - a critical skill for robots to operate in the unstructured 3D world.
Fit2Form: 3D Generative Model for Robot Gripper Form Design
We propose Fit2Form, a 3D generative design framework that generates pairs of finger shapes to maximize design objectives (i. e., grasp success, stability, and robustness) for target grasp objects.
Learning a Decentralized Multi-arm Motion Planner
In this paper, we tackle this problem with multi-agent reinforcement learning, where a decentralized policy is trained to control one robot arm in the multi-arm system to reach its target end-effector pose given observations of its workspace state and target end-effector pose.
