CC-VPSTO: Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation for Online Robot Motion Planning Under Uncertainty
(2026) The International Journal of Robotics Research — (2026)
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brudermüller-et-al-2026-cc-vpsto-chance-constrained-via-point-based-stochastic-trajectory-optimisation-for-online-robot.pdf
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- Authors
Brudermüller, Lara 
Jankowski, Julius Bhattacharyya, Raunak
- Abstract
- Reliable robot autonomy hinges on decision-making systems that account for uncertainty without imposing overly conservative restrictions on the robot's action space. We introduce Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation (CC-VPSTO), a real-time capable framework for generating task-efficient robot trajectories that satisfy constraints with high probability by formulating stochastic control as a chance-constrained optimisation problem. Since such problems are generally intractable, we propose a deterministic surrogate formulation based on Monte Carlo sampling, solved efficiently with gradient-free optimisation. To address bias in naïve sampling approaches, we quantify approximation error and introduce padding strategies to improve reliability. We focus on three challenges: (i) sample-efficient constraint approximation, (ii) conditions for surrogate solution validity, and (iii) online optimisation. Integrated into a receding-horizon MPC framework, CC-VPSTO enables reactive, task-efficient control under uncertainty, balancing constraint satisfaction and performance in a principled manner. The strengths of our approach lie in its generality, that is, no assumptions on the underlying uncertainty distribution, system dynamics, cost function, or the form of inequality constraints; and its applicability to online robot motion planning. We demonstrate the validity and efficiency of our approach in both simulation and on a Franka Emika robot. Videos and additional material are made available here: https:// sites.google.com/oxfordrobotics.institute/cc-vpsto.
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Citations
Brudermüller, L., Berger, G., Jankowski, J., Bhattacharyya, R., Calinon, S., Jungers, R., & Hawes, N. (2026). CC-VPSTO: Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation for Online Robot Motion Planning Under Uncertainty. The International Journal of Robotics Research. Published. https://doi.org/10.1177/02783649261464639 (Original work published 2026)