7 papers
Nano-U: Efficient Terrain Segmentation for Tiny Robot Navigation
Federico Pizzolato, Francesco Pasti, Nicola Bellotto
Terrain segmentation is a fundamental capability for autonomous mobile robots operating in unstructured outdoor environments. However, state-of-the-art models are incompatible with…
TiROD: Tiny Robotics Dataset and Benchmark for Continual Object Detection
Francesco Pasti, Riccardo De Monte, Davide Dalle Pezze +2
Detecting objects with visual sensors is crucial for numerous mobile robotics applications, from autonomous navigation to inspection. However, robots often need to operate under si…
Minimalist Visual Inertial Odometry
Francesco Pasti, Jeremy Klotz, Nicola Bellotto +1
Visual-Inertial Odometry(VIO), which is critical to mobile robot navigation, uses cameras with a large number of pixels. Capturing and processing camera images requires significant…
Replay Consolidation with Label Propagation for Continual Object Detection
Riccardo De Monte, Davide Dalle Pezze, Marina Ceccon +5
Continual Learning (CL) aims to learn new data while remembering previously acquired knowledge. In contrast to CL for image classification, CL for Object Detection faces additional…
MicroFlow: An Efficient Rust-Based Inference Engine for TinyML
Matteo Carnelos, Francesco Pasti, Nicola Bellotto
In recent years, there has been a significant interest in developing machine learning algorithms on embedded systems. This is particularly relevant for bare metal devices in Intern…
Latent Distillation for Continual Object Detection at the Edge
Francesco Pasti, Marina Ceccon, Davide Dalle Pezze +4
While numerous methods achieving remarkable performance exist in the Object Detection literature, addressing data distribution shifts remains challenging. Continual Learning (CL) o…