Ilyass Taouil — accepted AI-conference papers

2025

Non-Gaited Legged Locomotion With Monte-Carlo Tree Search and Supervised Learning

Ilyass Taouil, Lorenzo Amatucci, Majid Khadiv, Angela Dai, Victor Barasuol, Giulio Turrisi +1

RA-L 2025

Legged robots are able to navigate complex terrains by continuously interacting with the environment through careful selection of contact sequences and timings. However, the combinatorial nature behind contact planning hinders the applicability of such optimization problems on hardware. In this work

Cited by 8 Source ↗Scholar ↗

2023

Quadrupedal Footstep Planning Using Learned Motion Models of a Black-Box Controller

Ilyass Taouil, Giulio Turrisi, Daniel Schleich, Victor Barasuol, Claudio Semini, Sven Behnke

IROS 2023poster

Legged robots are increasingly entering new domains and applications, including search and rescue, inspection, and logistics. However, for such a systems to be valuable in real-world scenarios, they must be able to autonomously and robustly navigate irregular terrains. In many cases, robots that are…

Cited by 1 Source ↗Scholar ↗