8 papers · 1 filter
Self-Paced Curriculum Reinforcement Learning for Autonomous Superbike Racing in Simulation
Luca Ghisi, Jacopo Essenziale, Carlo D'Eramo +1
Autonomous Racing has seen remarkable progress through deep Reinforcement Learning (RL), primarily for four-wheeled vehicles. However, motorbikes introduce substantially greater co…
Instance-Guided Unsupervised Domain Adaptation for Robotic Semantic Segmentation
Michele Antonazzi, Lorenzo Signorelli, Matteo Luperto +1
Semantic segmentation networks, which are essential for robotic perception, often suffer from performance degradation when the visual distribution of the deployment environment dif…
Development and Adaptation of Robotic Vision in the Real-World: the Challenge of Door Detection
Michele Antonazzi, Matteo Luperto, N. Alberto Borghese +1
Mobile service robots are increasingly prevalent in human-centric, real-world domains, operating autonomously in unconstrained indoor environments. In such a context, robotic visio…
Biasing Frontier-Based Exploration with Saliency Areas
Matteo Luperto, Valerii Stakanov, Giacomo Boracchi +2
Autonomous exploration is a widely studied problem where a robot incrementally builds a map of a previously unknown environment. The robot selects the next locations to reach using…
Robust Localization, Mapping, and Navigation for Quadruped Robots
Dyuman Aditya, Junning Huang, Nico Bohlinger +5
Quadruped robots are currently a widespread platform for robotics research, thanks to powerful Reinforcement Learning controllers and the availability of cheap and robust commercia…
Frontier-Based Exploration for Multi-Robot Rendezvous in Communication-Restricted Unknown Environments
Mauro Tellaroli, Matteo Luperto, Michele Antonazzi +1
Multi-robot rendezvous and exploration are fundamental challenges in the domain of mobile robotic systems. This paper addresses multi-robot rendezvous within an initially unknown e…