Author: Francesco Verdoja
Video on “Probabilistic Surface Friction Estimation Based on Visual and Haptic Measurements”
Watch the video demonstration of our latest paper on friction coefficient estimation
Master thesis on “People flow maps for indoor robot navigation”
This thesis goal is to develop a probabilistic approach for building and updating people flow maps able to help the robot being socially-aware while navigating by predicting people movement.
Video Presentation at PAL workshop @ ICRA2020 “On the Potential of Smarter Multi-layer Maps in Robotics”
Watch the video presentation of our latest paper in the Hypermaps project
Hypermaps at PAL ICRA 2020 workshop
We presented the core idea behind the Hypermaps project at the ICRA 2020 workshop on Perception, Action, Learning (PAL)
Hypermaps: Beyond Occupancy Grids
Hypermaps aim at improving how robots manage data about the environment they inhabit.
Occupancy Uncertainty Maps
In this project we research how to build maps which include the uncertainty of the robot over the occupancy of the objects in the environment.
We have shown how the constructed maps can be used to increase global navigation safety by planning trajectories which avoid areas of high uncertainty, enabling higher autonomy for mobile robots in indoor settings.
Dataset for “Hallucinating Robots”
We released the dataset for our IROS 2018 paper “Hallucinating Robots: Inferring Obstacle Distances from Partial Laser Measurements”.