3 papers
cs.RO2026
Self-supervised Domain Adaptation for Visual 3D Pose Estimation of Nano-drone Racing Gates by Enforcing Geometric Consistency
Nicholas Carlotti, Michele Antonazzi, Elia Cereda +4
We consider the task of visually estimating the relative pose of a drone racing gate in front of a nano-quadrotor, using a convolutional neural network pre-trained on simulated dat…
cs.RO2026
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…
cs.RO2025
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…