Andreu Matoses Gimenez — accepted AI-conference papers

2026

Cross-Entropy Optimization of Physically Grounded Task and Motion Plans

Andreu Matoses Gimenez, Nils Wilde, Christian Pek, Javier Alonso-Mora

RA-L 2026

Autonomously performing tasks often requires robots to plan high-level discrete actions and continuous low-level motions to realize them. Previous TAMP algorithms have focused mainly on computational performance, completeness, or optimality by making the problem tractable through simplifications and

Cited by 0 Source ↗Scholar ↗

2025

Decentralized Aerial Manipulation of a Cable-Suspended Load Using Multi-Agent Reinforcement Learning

Jack Zeng, Andreu Matoses Gimenez, Eugene Vinitsky, Javier Alonso-Mora, Sihao Sun

CoRL 2025poster

This paper presents the first decentralized method to enable real-world 6-DoF manipulation of a cable-suspended load using a team of Micro-Aerial Vehicles (MAVs). Our method leverages multi-agent reinforcement learning (MARL) to train an outer-loop control policy for each MAV. Unlike state-of-the-ar…

Cited by 13 Source ↗Scholar ↗