Simon Wasiela — accepted AI-conference papers

2024

Robust Motion Planning With Accuracy Optimization Based on Learned Sensitivity Metrics

Simon Wasiela, Marco Cognetti, Paolo Robuffo Giordano, Juan Cortés, Thierry Siméon

RA-L 2024

This letter addresses the problem of generating robust and accurate trajectories taking into account uncertainties in the robot dynamic model. Based on the notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">closed-loop sensitivity</i>, which q

Cited by 3 Source ↗Scholar ↗

2023

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

Simon Wasiela, Paolo Robuffo Giordano, Juan Cortés, Thierry Siméon

ICRA 2023poster

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 in [1], [2] to generate…

Cited by 17 Source ↗Scholar ↗