14 papers
Hierarchical Topology-Aware Planning and Control of Underwater Vehicle-Manipulator Systems in Confined Environments
Mohamed Abdelwahab, Ruggero Carli, Damiano Varagnolo +1
This paper addresses autonomous intervention with an underwater vehicle--manipulator system (UVMS) in confined, cluttered, and partially known environments, where poor maneuverabil…
Real2Sim via Active Perception with Behavior Trees Automatically Generated by VLMs
Alessandro Adami, Sebastian Zudaire, Ruggero Carli +1
Constructing physically accurate simulation environments (Real2Sim) traditionally relies on manual system identification or rigid, exhaustive exploration routines. These task-agnos…
Learning Structured Robot Policies from Vision-Language Models via Synthetic Neuro-Symbolic Supervision
Alessandro Adami, Tommaso Tubaldo, Marco Todescato +2
Vision-Language Models (VLMs) have recently demonstrated strong capabilities in mapping multimodal observations to robot behaviors. However, most current approaches rely on end-to-…
Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems
Jing Liu, Yangyang Yang, Luca Ballotta +3
This paper studies multi-agent reinforcement learning with submodular team utilities for online distributed task allocation. In this setting, each agent selects one action from a l…
Learning Stack-of-Tasks Management for Redundant Robots
Alessandro Adami, Aris Synodinos, Matteo Iovino +2
This paper presents a novel framework for automatically learning complete Stack-of-Tasks (SoT) controllers for redundant robotic systems, including task priorities, activation logi…
Edge Delayed Deep Deterministic Policy Gradient: efficient continuous control for edge scenarios
Alberto Sinigaglia, Niccolò Turcato, Ruggero Carli +1
Deep Reinforcement Learning is gaining increasing attention thanks to its capability to learn complex policies in high-dimensional settings. Recent advancements utilize a dual-netw…