8 papers · 1 filter
LeCropFollow: Latent Space Planning for Navigation in Unstructured Crop Fields
Felipe Tommaselli, Francisco Affonso, Arthur Pompeu +4
Unstructured navigational features, such as irregular planting or discontinuities, remain the primary failure mode for under-canopy agricultural robots. Existing geometric approach…
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…
CropNav: a Framework for Autonomous Navigation in Real Farms
Mateus Valverde Gasparino, Vitor Akihiro Hisano Higuti, Arun Narenthiran Sivakumar +3
Small robots that can operate under the plant canopy can enable new possibilities in agriculture. However, unlike larger autonomous tractors, autonomous navigation for such under c…
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,…
PlantTrack: Task-Driven Plant Keypoint Tracking with Zero-Shot Sim2Real Transfer
Samhita Marri, Arun N. Sivakumar, Naveen K. Uppalapati +1
Tracking plant features is crucial for various agricultural tasks like phenotyping, pruning, or harvesting, but the unstructured, cluttered, and deformable nature of plant environm…