Fast-Grasp'D: Dexterous Multi-finger Grasp Generation Through Differentiable Simulation
Dylan Turpin,Tao Zhong,Shutong Zhang,Guanglei Zhu,Eric Heiden,Miles Macklin,Stavros Tsogkas,Sven Dickinson,Animesh Garg,Dylan Turpin,Tao Zhong,Shutong Zhang,Guanglei Zhu,Eric Heiden,Miles Macklin,Stavros Tsogkas,Sven Dickinson,Animesh Garg
Multi-finger grasping relies on high quality training data, which is hard to obtain: human data is hard to transfer and synthetic data relies on simplifying assumptions that reduce grasp quality. By making grasp simulation differentiable, and contact dynamics amenable to gradient-based optimization, we accelerate the search for high-quality grasps with fewer limiting assumptions. We present Grasp'...
