8 citations · 8 across the 17 of their papers we have counts for
18 papers
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…
THREAD: Trajectory Planning for Hybrid Rigid-Soft Manipulators with Environment-Aware Diffusion
Shivani Kamtikar, Pranav Asthana, Naveen Kumar Uppalapati +2
Manipulation in confined environments, such as threading a manipulator through narrow apertures, remains a fundamental challenge, especially for conventional rigid robots. Hybrid r…
CTS-MoE: Implicit Terrain Adaptation via Mixture-of-Experts for Perceptive Locomotion
Francisco Affonso, Matheus P. Angarola, Ana Luiza Mineiro +3
Perceptive legged locomotion over discontinuous terrain (e.g., stairs, gaps, and obstacles) requires adaptive behavior, as a single conservative gait cannot produce the anticipator…
CATNAV: Cached Vision-Language Traversability for Efficient Zero-Shot Robot Navigation
Aditya Potnis, Francisco Affonso, Shreya Gummadi +2
Navigating unstructured environments requires assessing traversal risk relative to a robot's physical capabilities, a challenge that varies across embodiments. We present CATNAV, a…
HyReach: Vision-Guided Hybrid Manipulator Reaching in Unseen Cluttered Environments
Shivani Kamtikar, Kendall Koe, Justin Wasserman +5
As robotic systems increasingly operate in unstructured, cluttered, and previously unseen environments, there is a growing need for manipulators that combine compliance, adaptabili…
OctoSplat: Hybrid OctoMap-Gaussian Splatting for Active Semantic Mapping and Phenotyping with Horticultural Robots
Jose Cuaran, Naveen K. Uppalapati, Girish Chowdhary
Semantic reconstruction of agricultural scenes plays a vital role in tasks such as phenotyping and yield estimation. However, traditional approaches based on manual scanning or fix…
Visual-Language-Guided Task Planning for Horticultural Robots
Jose Cuaran, Kendall Koe, Aditya Potnis +2
Crop monitoring is essential for precision agriculture, but current systems lack high-level reasoning. We introduce a novel, modular framework that uses a Vision Language Model (VL…
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…
Learning to Walk With Less: A Dyna-Style Approach to Quadrupedal Locomotion
Francisco Affonso, Felipe Tommaselli, João H. Aléssio +4
Traditional on-policy reinforcement learning (RL) controllers for quadrupedal locomotion often suffer from low data efficiency, requiring millions of interactions with simulated en…
ZeST: A VLM-based Zero-Shot Traversability Navigation for Unknown Environments
Shreya Gummadi, Mateus V. Gasparino, Gianluca Capezzuto +2
Advances in robotics and autonomous navigation systems hinge on the ability to predict terrain traversability accurately. Traditional methods for generating datasets to train these…
BYON: Bring Your Own Networks for Digital Agriculture Applications
Emerson Sie, Bill Tao, Aganze Mihigo +5
Digital agriculture technologies rely on sensors, drones, robots, and autonomous farm equipment to improve farm yields and incorporate sustainability practices. However, the adopti…
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…
Exploitation-Guided Exploration for Semantic Embodied Navigation
Justin Wasserman, Girish Chowdhary, Abhinav Gupta +1
In the recent progress in embodied navigation and sim-to-robot transfer, modular policies have emerged as a de facto framework. However, there is more to compositionality beyond th…