4 papers
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…
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…