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Conference Papers Year : 2023

A Sensitivity-Aware Motion Planner (SAMP) to Generate Intrinsically-Robust Trajectories

Simon Wasiela
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Juan Cortés
Thierry Simeon


Closed-loop state sensitivity [1], [2] is a recently introduced notion that can be used to quantify deviations of the closed-loop trajectory of a robot/controller pair against variations of uncertain parameters in the robot model. While local optimization techniques are used to generate reference trajectories minimizing a sensitivity-based cost, no global planning algorithm considering this metric to compute collision-free motions robust to parametric uncertainties has yet been proposed. The contribution of this paper is to propose a global control-aware motion planner for optimizing a state sensitivity metric and producing collision-free reference motions that are robust against parametric uncertainties for a large class of complex dynamical systems. Given the prohibitively high computational cost of directly minimizing the state sensitivity using asymptotically optimal sampling-based tree planners, the proposed RRT*-based SAMP planner uses an appropriate steering method to first compute a (near) time-optimal and kinodynamically feasible trajectory that is then locally deformed to improve robustness and decrease its sensitivity to uncertainties. The evaluation performed on planar/full-3D quadrotor UAV models shows that the SAMP method produces low sensitivity robust solutions with a much higher performance than a planner directly optimizing the sensitivity.
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Dates and versions

hal-03808933 , version 1 (10-10-2022)
hal-03808933 , version 2 (06-03-2023)



  • HAL Id : hal-03808933 , version 2


Simon Wasiela, Paolo Robuffo Giordano, Juan Cortés, Thierry Simeon. A Sensitivity-Aware Motion Planner (SAMP) to Generate Intrinsically-Robust Trajectories. IEEE International Conference on Robotics and Automation (ICRA), 2023, London, United Kingdom. ⟨hal-03808933v2⟩
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