Meher V. R. Malladi
Papers
5
Total Citations
39
H-Index
4
About
Meher V. R. Malladi is a robotics researcher whose work sits at the intersection of agricultural and forestry automation, with a focus on enabling robots to perceive and adapt to dynamic, unstructured natural environments. Their core research areas include spatial-temporal mapping, LiDAR-based perception, and data association for changing scenes. Malladi’s major contributions center on developing systems that allow robots to track and model growing plants and forest environments over time—a critical challenge for automating phenotyping and sustainable forest management. Their work on estimating 4D data associations for agricultural robots (12 citations) and spatio-temporal consistent mapping for crops in the wild (4 citations) has laid foundational methods for robots to localize and adapt to heavily changing plant geometries. In forestry, Malladi contributed to the Digiforests longitudinal LiDAR dataset (9 citations) and developed techniques for tree instance segmentation and trait estimation (6 citations), enabling mobile robots to monitor forest ecosystems at scale. Their Kinematic-ICP method (8 citations) enhances odometry for wheeled robots on planar surfaces. With over 39 citations across these key papers, Malladi is shaping the future of field robotics in agriculture and forestry.
Research Focus
Key Achievements
Top Papers
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- 2Digiforests: a Longitudinal Lidar Dataset for Forestry Robotics9 citations · 2025
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