1 citations · 1 across the 3 of their papers we have counts for
6 papers
CoPlanVLM: Coordinated Path Planning for a Robot Team using Vision Language Models
David R. Martin, Jared Paquet, Mohammad Abdullah Al Faruque +4
We present CoPlanVLM, which uses a Vision Language Model (VLM) to translate a single natural-language instruction and image into coordinated paths for a team of two robots. While V…
CORNAV: Construction-Aware Reasoning for Robot Navigation on Active Worksites
Parastoo Ali Pour, Deepak Prakash Kumar, Tommy Zhou +2
The construction industry faces persistent labor shortages, low productivity that costs the global economy over $1.6 trillion annually, and one of the highest injury rates among ma…
Toward Humanoid Robots in Construction: A Teleoperation Feasibility Study
Parastoo Ali Pour, David R. Martin, Chang Min Hur +6
We present a teleoperation system that enables a single operator to perform construction tasks on a Unitree G1 humanoid, combining extended reality (XR) based upper body control wi…
CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving
Junyao Wang, Yulin Xu, Yu Li +2
Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception. However, robust cross-modal feature fu…
HydraCollab: Adaptive Collaborative-Perception for Distributed Autonomous Systems
Luke Chen, Cheng-Ju Wu, David R. Martin +3
Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information. Existing collaborative-perception systems face an inherent…
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception
Luke Chen, Junyao Wang, Trier Mortlock +2
Uncertainty Quantification (UQ) is crucial for ensuring the reliability of machine learning models deployed in real-world autonomous systems. However, existing approaches typically…