activity
20182026
most citedBuilding an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution

139 citations · 308 across the 23 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.RO2024★ 2 cited

Markerless Aerial-Terrestrial Co-Registration of Forest Point Clouds using a Deformable Pose Graph

Benoit Casseau, Nived Chebrolu, Matias Mattamala +2

For biodiversity and forestry applications, end-users desire maps of forests that are fully detailed, from the forest floor to the canopy. Terrestrial laser scanning and aerial las…

cs.RO2024★ 2 cited

Autonomous Forest Inventory with Legged Robots: System Design and Field Deployment

Matías Mattamala, Nived Chebrolu, Benoit Casseau +5

We present a solution for autonomous forest inventory with a legged robotic platform. Compared to their wheeled and aerial counterparts, legged platforms offer an attractive balanc…

cs.RO2024★ 2 cited

Wild Visual Navigation: Fast Traversability Learning via Pre-Trained Models and Online Self-Supervision

Matías Mattamala, Jonas Frey, Piotr Libera +5

Natural environments such as forests and grasslands are challenging for robotic navigation because of the false perception of rigid obstacles from high grass, twigs, or bushes. In…

cs.RO2024★ 27 cited

SiLVR: Scalable Lidar-Visual Reconstruction with Neural Radiance Fields for Robotic Inspection

Yifu Tao, Yash Bhalgat, Lanke Frank Tarimo Fu +3

We present a neural-field-based large-scale reconstruction system that fuses lidar and vision data to generate high-quality reconstructions that are geometrically accurate and capt…

cs.RO2024★ 19 cited

Online Tree Reconstruction and Forest Inventory on a Mobile Robotic System

Leonard Freißmuth, Matias Mattamala, Nived Chebrolu +3

Terrestrial laser scanning (TLS) is the standard technique used to create accurate point clouds for digital forest inventories. However, the measurement process is demanding, requi…

cs.RO2024

Evaluation and Deployment of LiDAR-based Place Recognition in Dense Forests

Haedam Oh, Nived Chebrolu, Matias Mattamala +2

Many LiDAR place recognition systems have been developed and tested specifically for urban driving scenarios. Their performance in natural environments such as forests and woodland…