10 papers
Algorithmic design and implementation considerations of deep MPC
Prabhat K. Mishra, Mateus V. Gasparino, Girish Chowdhary
Deep Model Predictive Control (Deep MPC) is an evolving field that integrates model predictive control and deep learning. This manuscript is focused on a particular approach, which…
ZeST: an LLM-based Zero-Shot Traversability Navigation for Unknown Environments
Shreya Gummadi, Mateus V. Gasparino, Gianluca Capezzuto +2
The advancement of robotics and autonomous navigation systems hinges on the ability to accurately predict terrain traversability. Traditional methods for generating datasets to tra…
Learning to Walk With Less: A Dyna-Style Approach to Quadrupedal Locomotion
Francisco Affonso, Felipe Tommaselli, Felipe Andrade G. Tommaselli +6
Traditional on-policy reinforcement learning (RL) controllers for quadrupedal locomotion often suffer from low data efficiency, requiring millions of interactions with simulated en…
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…
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…