TR2025-150
Analytic Conditions for Differentiable Collision Detection in Trajectory Optimization
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- , "Analytic Conditions for Differentiable Collision Detection in Trajectory Optimization", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.BibTeX TR2025-150 PDF
- @inproceedings{Jaitly2025oct,
- author = {Jaitly, Akshay and Jha, Devesh K. and Ota, Kei and Shirai, Yuki},
- title = {{Analytic Conditions for Differentiable Collision Detection in Trajectory Optimization}},
- booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2025,
- month = oct,
- url = {https://www.merl.com/publications/TR2025-150}
- }
- , "Analytic Conditions for Differentiable Collision Detection in Trajectory Optimization", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2025.
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Abstract:
Optimization-based methods are widely used for computing fast, diverse solutions for complex tasks such as collision-free movement or planning in the presence of con- tacts. However, most of these methods require enforcing non- penetration constraints between objects, resulting in a non- trivial and computationally expensive problem. This makes the use of optimization-based methods for planning and control challenging. In this paper, we present a method to efficiently enforce non-penetration of sets while performing optimization over their configuration, which is directly applicable to problems like collision-aware trajectory optimization. We introduce novel differentiable conditions with analytic expressions to achieve this. To enforce non-collision between non-smooth bodies using these conditions, we introduce a method to approximate polytopes as smooth semi-algebraic sets. We present several numerical experiments to demonstrate the performance of the proposed method and compare the performance with other baseline methods recently proposed in the literature.

