55 citations · 68 across the 10 of their papers we have counts for
11 papers
Sampling-Based Coordination-Informed Multi-Objective Multi-Robot Reinforcement Learning
Antonio Marino, Esteban Restrepo, Soon-jo Chung +2
Multi-robot systems must simultaneously optimize competing objectives while maintaining coordinated behavior. Existing multi-agent reinforcement learning approaches often rely on f…
Impact-Robust Posture Optimization for Aerial Manipulation
Amr Afifi, Ahmad Gazar, Javier Alonso-Mora +2
We present a novel method for optimizing the posture of kinematically redundant torque-controlled robots to improve robustness during impacts. A rigid impact model is used as the b…
Decentralized Reinforcement Learning for Multi-Agent Multi-Resource Allocation via Dynamic Cluster Agreements
Antonio Marino, Esteban Restrepo, Claudio Pacchierotti +1
This paper addresses the challenge of allocating heterogeneous resources among multiple agents in a decentralized manner. Our proposed method, Liquid-Graph-Time Clustering-IPPO, bu…
Multi-UAVs end-to-end Distributed Trajectory Generation over Point Cloud Data
Antonio Marino, Claudio Pacchierotti, Paolo Robuffo Giordano
This paper introduces an end-to-end trajectory planning algorithm tailored for multi-UAV systems that generates collision-free trajectories in environments populated with both stat…
Liquid-Graph Time-Constant Network for Multi-Agent Systems Control
Antonio Marino, Claudio Pacchierotti, Paolo Robuffo Giordano
In this paper, we propose the Liquid-Graph Time-constant (LGTC) network, a continuous graph neural network(GNN) model for control of multi-agent systems based on therecent Liquid T…
Neural Style Transfer with Twin-Delayed DDPG for Shared Control of Robotic Manipulators
Raul Fernandez-Fernandez, Marco Aggravi, Paolo Robuffo Giordano +2
Neural Style Transfer (NST) refers to a class of algorithms able to manipulate an element, most often images, to adopt the appearance or style of another one. Each element is defin…
Input State Stability of Gated Graph Neural Networks
Antonio Marino, Claudio Pacchierotti, Paolo Robuffo Giordano
In this paper, we aim to find the conditions for input-state stability (ISS) and incremental input-state stability (ISS) of Gated Graph Neural Networks (GGNNs). We show that thi…
COP: Control & Observability-aware Planning
Christoph Böhm, Pascal Brault, Quentin Delamare +2
In this research, we aim to answer the question: How to combine Closed-Loop State and Input Sensitivity-based with Observability-aware trajectory planning? These possibly opposite…
A Fourier transform for all generalized functions
Akbarali Mukhammadiev, Diksha Tiwari, Paolo Giordano
Using the existence of infinite numbers in the non-Archimedean ring of Robinson-Colombeau, we define the hyperfinite Fourier transform (HFT) by considering integration extended…
Human-in-the-loop optimisation: mixed initiative grasping for optimally facilitating post-grasp manipulative actions
Amir M. Ghalamzan Esfahani, Firas Abi-Farraj, Paolo Robuffo Giordano +1
This paper addresses the problem of mixed initiative, shared control for master-slave grasping and manipulation. We propose a novel system, in which an autonomous agent assists a h…
Rigidity Theory in SE(2) for Unscaled Relative Position Estimation using only Bearing Measurements
Daniel Zelazo, Antonio Franchi, Paolo Robuffo Giordano
This work considers the problem of estimating the unscaled relative positions of a multi-robot team in a common reference frame from bearing-only measurements. Each robot has acces…