8 citations · 8 across the 17 of their papers we have counts for
6 papers · 1 filter
Active Semantic Mapping with Mobile Manipulator in Horticultural Environments
Jose Cuaran, Kulbir Singh Ahluwalia, Kendall Koe +2
Semantic maps are fundamental for robotics tasks such as navigation and manipulation. They also enable yield prediction and phenotyping in agricultural settings. In this paper, we…
MetaCropFollow: Few-Shot Adaptation with Meta-Learning for Under-Canopy Navigation
Thomas Woehrle, Arun N. Sivakumar, Naveen Uppalapati +1
Autonomous under-canopy navigation faces additional challenges compared to over-canopy settings - for example the tight spacing between the crop rows, degraded GPS accuracy and exc…
Fed-EC: Bandwidth-Efficient Clustering-Based Federated Learning For Autonomous Visual Robot Navigation
Shreya Gummadi, Mateus V. Gasparino, Deepak Vasisht +1
Centralized learning requires data to be aggregated at a central server, which poses significant challenges in terms of data privacy and bandwidth consumption. Federated learning p…
AdaCropFollow: Self-Supervised Online Adaptation for Visual Under-Canopy Navigation
Arun N. Sivakumar, Federico Magistri, Mateus V. Gasparino +3
Under-canopy agricultural robots can enable various applications like precise monitoring, spraying, weeding, and plant manipulation tasks throughout the growing season. Autonomous…
Learning to Turn: Diffusion Imitation for Robust Row Turning in Under-Canopy Robots
Arun N. Sivakumar, Pranay Thangeda, Yixiao Fang +4
Under-canopy agricultural robots require robust navigation capabilities to enable full autonomy but struggle with tight row turning between crop rows due to degraded GPS reception,…
WayFASTER: a Self-Supervised Traversability Prediction for Increased Navigation Awareness
Mateus Valverde Gasparino, Arun Narenthiran Sivakumar, Girish Chowdhary
Accurate and robust navigation in unstructured environments requires fusing data from multiple sensors. Such fusion ensures that the robot is better aware of its surroundings, incl…