4 papers · 1 filter
OASIS-Map: Object-Level Change Detection in Multi-Session Mapping using Semantic Correspondence Matching
Haedam Oh, Yifu Tao, Nived Chebrolu +1
Map representations which are consistent across repeated visits to a real-world semi-static environment are very useful for long-term robotic inspection. In such settings, the scen…
TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory
Minwoo Jung, Dongjae Lee, Nived Chebrolu +3
Reliable localization is essential for sustainable forest management, as it allows robots to revisit and monitor the status of individual trees over long periods. In modern forestr…
TreeLoc: 6-DoF LiDAR Global Localization in Forests via Inter-Tree Geometric Matching
Minwoo Jung, Nived Chebrolu, Lucas Carvalho de Lima +3
Reliable localization is crucial for navigation in forests, where GPS is often degraded and LiDAR measurements are repetitive, occluded, and structurally complex. These conditions…
Building Forest Inventories with Autonomous Legged Robots -- System, Lessons, and Challenges Ahead
Matías Mattamala, Nived Chebrolu, Jonas Frey +5
Legged robots are increasingly being adopted in industries such as oil, gas, mining, nuclear, and agriculture. However, new challenges exist when moving into natural, less-structur…