Guillaume de Mathelin de Papigny — accepted AI-conference papers

2026

F-RRT: An Efficient Algorithm for Semi-Constrained Path Planning Problems

Guillaume de Mathelin de Papigny, Franco Gassibe, Vincent Padois

RA-L 2026

This paper addresses the challenging problem of Semi-Constrained End-Effector Path Planning for robotic manipulators. This problem arises when complex specifications restrict the end-effector's motion during the execution of industrial tasks. Traditional path planning algorithms often struggle with

Cited by 0 Source ↗Scholar ↗

2026

F-RRT: An Efficient Algorithm for Semi-Constrained Path Planning Problems

Guillaume de Mathelin de Papigny, Franco Ivan Gassibe, Vincent Padois

ICRA 2026poster

This letter addresses the challenging problem of Semi-Constrained End-Effector Path Planning for robotic manipulators. This problem arises when complex specifications restrict the end-effector’s motion during the execution of industrial tasks. Traditional path planning algorithms often struggle with…

Cited by 0 Source ↗Scholar ↗