7 papers
ZiMPedance: Impedance-Aware ZMP Modeling and Control for Payload Carrying with Quadruped Robots
Giovanni B. Dessy, Lorenzo Amatucci, Victor Barasuol +1
Load transportation with quadruped robots is strongly affected by the dynamics of the physical interface between the robot and the load. Passive spring-based arms reduce weight and…
Primal-Dual iLQR for GPU-Accelerated Learning and Control in Legged Robots
Lorenzo Amatucci, João Sousa-Pinto, Giulio Turrisi +3
This paper introduces a novel Model Predictive Control (MPC) implementation for legged robot locomotion that leverages GPU parallelization. Our approach enables both temporal and s…
Non-Gaited Legged Locomotion with Monte-Carlo Tree Search and Supervised Learning
Ilyass Taouil, Lorenzo Amatucci, Majid Khadiv +4
Legged robots are able to navigate complex terrains by continuously interacting with the environment through careful selection of contact sequences and timings. However, the combin…
MUSE: A Real-Time Multi-Sensor State Estimator for Quadruped Robots
Ylenia Nisticò, João Carlos Virgolino Soares, Lorenzo Amatucci +2
This paper introduces an innovative state estimator, MUSE (MUlti-sensor State Estimator), designed to enhance state estimation's accuracy and real-time performance in quadruped rob…
Accelerating Model Predictive Control for Legged Robots through Distributed Optimization
Lorenzo Amatucci, Giulio Turrisi, Angelo Bratta +2
This paper presents a novel approach to enhance Model Predictive Control (MPC) for legged robots through Distributed Optimization. Our method focuses on decomposing the robot dynam…
On the Benefits of GPU Sample-Based Stochastic Predictive Controllers for Legged Locomotion
Giulio Turrisi, Valerio Modugno, Lorenzo Amatucci +2
Quadrupedal robots excel in mobility, navigating complex terrains with agility. However, their complex control systems present challenges that are still far from being fully addres…