By learning and integrating a gradient-consistent pose classifier into a differentiable rendering pipeline, the generated pose trajectories are free from physical collisions. The objective is to penalize high collision probabilities during optimization.

Prof. Robot: Differentiable Robot Rendering Without Static and Self-Collisions

Differentiable rendering has gained significant attention in the field of robotics, with differentiable robot rendering emerging as an effective paradigm for learning robotic actions from image-space supervision. However, the lack of physical world perception in this approach may lead to potential collisions during action optimization. In this work, we introduce a novel improvement on previous efforts by incorporating physical awareness of collisions through the learning of a neural robotic collision classifier....

March 14, 2025 · 2 min · 229 words · Quanyuan Ruan, Jiabao Lei, Wenhao Yuan, Yanglin Zhang, Dekun Lu, Guiliang Liu, Kui Jia