56 citations · 111 across the 25 of their papers we have counts for
20 papers · 1 filter
CAST: Alternating State-Value Targets and Expanded Policy Gradients for Model-Based Reinforcement Learning
Pietro Noah Crestaz, Mohamed Yassine Kabouri, Nicolas Mansard +1
Model-based reinforcement learning (MBRL) is a family of RL methods that learn a model of the environment and use it for action selection, making it well suited to robotics due to…
Towards safe and optimal flight: Viability Kernel MPC for Fully Actuated Multirotor
Massimiliano Bertoni, Alberto Piccina, Gianni Lunardi +4
Industrial aerial robotics demands safety guarantees for navigation in unstructured environments while optimizing performance and computational efficiency. This paper presents a me…
PAC-DP: PAC-Bayesian Diffusion Policy Learning
Mohammad Hasan Yeganegi, Dian Yu, Andrea Del Prete +2
Diffusion Policies (DPs) are able to perform complex manipulation tasks. However, DPs are typically trained by minimizing a denoising objective, which provides limited control over…
ALPINE: a climbing robot for operations in mountain environments
Michele Focchi, Andrea Del Prete, Daniele Fontanelli +3
Mountain slopes are perfect examples of harsh environments in which humans are required to perform difficult and dangerous operations such as removing unstable boulders, dangerous…
CACTO-SL: Using Sobolev Learning to improve Continuous Actor-Critic with Trajectory Optimization
Elisa Alboni, Gianluigi Grandesso, Gastone Pietro Rosati Papini +2
Trajectory Optimization (TO) and Reinforcement Learning (RL) are powerful and complementary tools to solve optimal control problems. On the one hand, TO can efficiently compute loc…
Efficient Reinforcement Learning for Jumping Monopods
Riccardo Bussola, Michele Focchi, Andrea Del Prete +2
In this work, we consider the complex control problem of making a monopod reach a target with a jump. The monopod can jump in any direction and the terrain underneath its foot can…
Receding-Constraint Model Predictive Control using a Learned Approximate Control-Invariant Set
Gianni Lunardi, Asia La Rocca, Matteo Saveriano +1
In recent years, advanced model-based and data-driven control methods are unlocking the potential of complex robotics systems, and we can expect this trend to continue at an expone…
Multi-contact Stochastic Predictive Control for Legged Robots with Contact Locations Uncertainty
Ahmad Gazar, Majid Khadiv, Andrea Del Prete +1
Trajectory optimization under uncertainties is a challenging problem for robots in contact with the environment. Such uncertainties are inevitable due to estimation errors, control…
Reactive Landing Controller for Quadruped Robots
Francesco Roscia, Michele Focchi, Andrea Del Prete +2
Quadruped robots are machines intended for challenging and harsh environments. Despite the progress in locomotion strategy, safely recovering from unexpected falls or planned drops…
VBOC: Learning the Viability Boundary of a Robot Manipulator using Optimal Control
Asia La Rocca, Matteo Saveriano, Andrea Del Prete
Safety is often the most important requirement in robotics applications. Nonetheless, control techniques that can provide safety guarantees are still extremely rare for nonlinear s…
CACTO: Continuous Actor-Critic with Trajectory Optimization -- Towards global optimality
Gianluigi Grandesso, Elisa Alboni, Gastone P. Rosati Papini +2
This paper presents a novel algorithm for the continuous control of dynamical systems that combines Trajectory Optimization (TO) and Reinforcement Learning (RL) in a single framewo…
CLIO: a Novel Robotic Solution for Exploration and Rescue Missions in Hostile Mountain Environments
Michele Focchi, Mohamed Bensaadallah, Marco Frego +4
Rescue missions in mountain environments are hardly achievable by standard legged robots-because of the high slopes-or by flying robots-because of limited payload capacity. We pres…
Orientation Control System: Enhancing Aerial Maneuvers for Quadruped Robots
Francesco Roscia, Andrea Cumerlotti, Andrea Del Prete +2
For legged robots, aerial motions are the only option to overpass obstacles that cannot be circumvent with standard locomotion gaits. In these cases, the robot must perform a leap…
Nonlinear Stochastic Trajectory Optimization for Centroidal Momentum Motion Generation of Legged Robots
Ahmad Gazar, Majid Khadiv, Sébastien Kleff +2
Generation of robust trajectories for legged robots remains a challenging task due to the underlying nonlinear, hybrid and intrinsically unstable dynamics which needs to be stabili…
Exponential Integration for Efficient and Accurate Multi-Body Simulation with Stiff Viscoelastic Contacts
Bilal Hammoud, Luca Olivieri, Ludovic Righetti +2
The simulation of multi-body systems with frictional contacts is a fundamental tool for many fields, such as robotics, computer graphics, and mechanics. Hard frictional contacts ar…
Solving Footstep Planning as a Feasibility Problem using L1-norm Minimization (Extended Version)
Daeun Song, Pierre Fernbach, Thomas Flayols +4
One challenge of legged locomotion on uneven terrains is to deal with both the discrete problem of selecting a contact surface for each footstep and the continuous problem of placi…
On Time Optimization of Centroidal Momentum Dynamics
Brahayam Ponton, Alexander Herzog, Andrea Del Prete +2
Recently, the centroidal momentum dynamics has received substantial attention to plan dynamically consistent motions for robots with arms and legs in multi-contact scenarios. Howev…
Partial Force Control of Constrained Floating-Base Robots
Andrea Del Prete, Nicolas Mansard, Francesco Nori +2
Legged robots are typically in rigid contact with the environment at multiple locations, which add a degree of complexity to their control. We present a method to control the motio…
Prioritized Optimal Control
Andrea Del Prete, Francesco Romano, Lorenzo Natale +3
This paper presents a new technique to control highly redundant mechanical systems, such as humanoid robots. We take inspiration from two approaches. Prioritized control is a wides…
Prioritized motion-force control of constrained fully-actuated robots: "Task Space Inverse Dynamics"
Andrea Del Prete, Francesco Nori, Giorgio Metta +1
We present a new framework for prioritized multi-task motion-force control of fully-actuated robots. This work is established on a careful review and comparison of the state of the…