Accepted Papers

The accepted papers can be found here: https://openreview.net/group?id=roboticsfoundation.org/RSS/2025/Workshop/Motion_Planning_and_Control_via_Parallelization

1. Antoine Groudiev, Shucheng Kang, Heng Yang, "cuADMM: GPU-Accelerated First-Order Optimization for Large-Scale Multi-Block Semidefinite Programs"

2. Jiaming Hu, Jiawei Wang, Henrik I Christensen, "cpRRTC: GPU-Parallel RRT-Connect for Constrained Motion Planning"

3. Kevin Tracy, Stefan Schaal, Yuval Tassa, Tom Erez, Jon Arrizabalaga, John Zhang, Zachary Manchester, "The Trajectory Bundle Method: Unifying Sequential-Convex Programming and Sampling-Based Trajectory Optimization"

4. An Thai Le, Khai Nguyen, Minh Nhat Vu, Joao Carvalho, Jan Peters, "Model Tensor Planning"

5. Max Muchen Sun, Jueun Kwon, Todd Murphey, "Scalable Coverage Trajectory Synthesis on GPUs as Statistical Inference"

6. Chaoyi Pan, Zeji Yi, Guanya Shi, Guannan Qu, "Toward Efficient and Stable Sampling-Based MPC via Large-scale Online Search"

7. Alexander Wachter, Minh Nhat Vu, "GPU-Accelerated Diffusion-Based NURBS Trajectory Optimization"

8. Albert H. Li, Brandon Hung, Aaron Ames, Jiuguang Wang, Simon Le Cleac'h, Preston Culbertson, "Judo: A User-Friendly Open-Source Package for Sampling-Based Model Predictive Control"

9. Andreu Matoses Gimenez, Christian Pek, Javier Alonso-Mora, "Cross-Entropy Optimization of Physically Grounded Task and Motion Plans"

10. Javier Borquez, Luke Raus, Yusuf Umut Ciftci, Somil Bansal, "DualGuard MPPI: Safe and Performant Optimal Control by Combining Sampling-Based MPC and Hamilton-Jacobi Reachability"

11. Jiarui Li, Alessandro Zanardi, Gioele Zardini, "Multi-Agent Path Finding via Finite-Horizon Hierarchical Factorization"

12. Jiahui Yang, Jason Jingzhou Liu, Yulong Li, Youssef Khaky, Kenneth Shaw, Deepak Pathak, "Deep Reactive Policy: Learning Reactive Manipulator Motion Planning for Dynamic Environments"

13. John Zhang, Zachary Manchester, "A Fast and Differentiable Interior-Point Solver for GPUs"

14. Jeremy S Morgan, David Millard, Gaurav S. Sukhatme, "CppFlow: Generative Inverse Kinematics for Efficient and Robust Cartesian Path Planning"