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Meher V. R. Malladi

7 accepted papers

2026

Robust Approach for LiDAR-Inertial Odometry Without Sensor-Specific Modeling

RA-L 2026

Accurate odometry is a critical component in a robotic navigation stack, and subsequent modules such as planning and control often rely on an estimate of the robot’s motion. LiDAR-based odometry approaches should be robust across sensor types and deployable in different target domains, from solid-st

Cited by 6SourcecodeScholar
2025

3D Hierarchical Panoptic Segmentation in Real Orchard Environments Across Different Sensors

IROS 2025

Crop yield estimation is a relevant problem in agriculture, because an accurate yield estimate can support farmers’ decisions on harvesting or precision intervention. Robots can help to automate this process. To do so, they need to be able to perceive the surrounding environment to identify target o

Cited by 1SourcecodeScholar
2025

Digiforests: a Longitudinal Lidar Dataset for Forestry Robotics

ICRA 2025

Forests are vital to our ecosystems, acting as carbon sinks, climate stabilizers, biodiversity centers, and wood sources. Due to their scale, monitoring and managing forests takes a lot of work. Forestry robotics offers the potential for enabling efficient and sustainable foresting practices through

Cited by 12SourceScholar
2025

Spatio-Temporal Consistent Semantic Mapping for Robotics Fruit Growth Monitoring

RA-L 2025

Automatic fruit growth monitoring plays a vital role in advancing precision agriculture. Tracking the evolution of fruits over time is essential to monitor their development and optimize production. The ability to recognize fruits over periods of time, even with drastic scene changes, is a required

Cited by 4SourceScholar
2024

Spatio-Temporal Consistent Mapping of Growing Plants for Agricultural Robots in the Wild

IROS 2024poster

Tracking changes in growing plants is important for automating phenotyping and robots managing crops. In this paper, we propose a system that uses a 3D model of plants along crop rows to enable a robotic platform to localize itself even in the presence of heavy changes and deforming the model to ada…

Cited by 2SourceScholar
2024

Tree Instance Segmentation and Traits Estimation for Forestry Environments Exploiting LiDAR Data Collected by Mobile Robots

ICRA 2024poster

Forests play a crucial role in our ecosystems, functioning as carbon sinks, climate stabilizers, biodiversity hubs, and sources of wood. By the very nature of their scale, monitoring and maintaining forests is a challenging task. Robotics in forestry can have the potential for substantial automation…

Cited by 5SourceScholar
2023

Estimating 4D Data Associations Towards Spatial-Temporal Mapping of Growing Plants for Agricultural Robots

IROS 2023poster

Our world is non-static, and robots should be able to track its changing geometry. For tracking changes, data asso-ciations between 3D points over time are key. In this paper, we investigate the problem of associating 3D points on plant organs from different mapping runs over time while the plants g…

Cited by 11SourceScholar