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CC-VPSTO: Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation for Online Robot Motion Planning Under Uncertainty

delete2026-07-16
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PRE
AI
L
Lara Brudermüller
G
Guillaume O. Berger
J
Julius Jankowski
R
Raunak Bhattacharyya
S
Sylvain Calinon
R
Raphaël M. Jungers
N
Nick Hawes
DOI:10.1177/02783649261464639delete
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Abstract

Abstract

En 中文
<jats:p> 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 <jats:italic toggle="yes">Chance-Constrained Via-Point-Based Stochastic Trajectory Optimisation</jats:italic> ( <jats:italic toggle="yes">CC</jats:italic> - <jats:italic toggle="yes">VPSTO</jats:italic> ), 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: <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://sites.google.com/oxfordrobotics.institute/cc-vpsto">https://sites.google.com/oxfordrobotics.institute/cc-vpsto</jats:ext-link> . </jats:p>

Journal

International Journal of Robotics Research cover
International Journal of Robotics Research
IF:
5
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2.4K
Citations:
1.5W

Organization

U
uclouvain
Scholars:
566
Papers: 260
Citations: 54
I
idiap research institute
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43
Papers: 21
Citations: 0
U
university of oxford
Scholars:
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Papers: 8.5W
Citations: 137
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