Publications (7)
GO: The Great Outdoors Multimodal Dataset
Peng Jiang, Kasi Viswanath, Akhil Nagariya +8
The Great Outdoors (GO) dataset is a multi-modal annotated data resource aimed at advancing ground robotics research in unstructured environments. Existing off-road datasets often…
CoPeD-Advancing Multi-Robot Collaborative Perception: A Comprehensive Dataset in Real-World Environments
Yang Zhou, Long Quang, Carlos Nieto-Granda +1
In the past decade, although single-robot perception has made significant advancements, the exploration of multi-robot collaborative perception remains largely unexplored. This inv…
Self-Reflective Terrain-Aware Robot Adaptation for Consistent Off-Road Ground Navigation
Sriram Siva, Maggie Wigness, John G. Rogers +2
Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as…
Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learned
Yulun Tian, Yun Chang, Long Quang +4
This paper revisits Kimera-Multi, a distributed multi-robot Simultaneous Localization and Mapping (SLAM) system, towards the goal of deployment in the real world. In particular, th…
NAUTS: Negotiation for Adaptation to Unstructured Terrain Surfaces
Sriram Siva, Maggie Wigness, John G. Rogers +2
When robots operate in real-world off-road environments with unstructured terrains, the ability to adapt their navigational policy is critical for effective and safe navigation. Ho…
NeuroMesh: A Unified Neural Inference Framework for Decentralized Multi-Robot Collaboration
Yang Zhou, Yash Shetye, Long Quang +8
Deploying learned multi-robot models on heterogeneous robots remains challenging due to hardware heterogeneity, communication constraints, and the lack of a unified execution stack…
Real-World Deployment of a Hierarchical Uncertainty-Aware Collaborative Multiagent Planning System
Martina Stadler Kurtz, Samuel Prentice, Yasmin Veys +5
We would like to enable a collaborative multiagent team to navigate at long length scales and under uncertainty in real-world environments. In practice, planning complexity scales…