7 papers
BIEVR-LIO: Robust LiDAR-Inertial Odometry through Bump-Image-Enhanced Voxel Maps
Patrick Pfreundschuh, Turcan Tuna, Cedric Le Gentil +3
Reliable odometry is essential for mobile robots as they increasingly enter more challenging environments, which often contain little information to constrain point cloud registrat…
DigiForest: Digital Analytics and Robotics for Sustainable Forestry
Marco Camurri, Enrico Tomelleri, MatÃas Mattamala +18
Covering one third of Earth's land surface, forests are vital to global biodiversity, climate regulation, and human well-being. In Europe, forests and woodlands reach approximately…
Semantic Landmark Particle Filter for Robot Localisation in Vineyards
Rajitha de Silva, Jonathan Cox, James R. Heselden +3
Reliable localisation in vineyards is hindered by row-level perceptual aliasing: parallel crop rows produce nearly identical LiDAR observations, causing geometry-only and vision-ba…
Semantic-Aware Particle Filter for Reliable Vineyard Robot Localisation
Rajitha de Silva, Jonathan Cox, James R. Heselden +3
Accurate localisation is critical for mobile robots in structured outdoor environments, yet LiDAR-based methods often fail in vineyards due to repetitive row geometry and perceptua…
Sight Over Site: Perception-Aware Reinforcement Learning for Efficient Robotic Inspection
Richard Kuhlmann, Jakob Wolfram, Boyang Sun +4
Autonomous inspection is a central problem in robotics, with applications ranging from industrial monitoring to search-and-rescue. Traditionally, inspection has often been reduced…
FrontierNet: Learning Visual Cues to Explore
Boyang Sun, Hanzhi Chen, Stefan Leutenegger +3
Exploration of unknown environments is crucial for autonomous robots; it allows them to actively reason and decide on what new data to acquire for different tasks, such as mapping,…