1 citations · 1 across the 10 of their papers we have counts for
10 papers
Failing Gracefully: Mitigating Impact of Inevitable Robot Failures
Duc M. Nguyen, Saad A. Ghani, Andrew Marshall +3
Service robots operate in household environments shared with humans, pets, and everyday objects, where they are highly susceptible to failures such as software crashes, hardware de…
E-SocialNav: Efficient Socially Compliant Navigation with Language Models
Ling Xiao, Daeun Song, Xuesu Xiao +1
Language models (LMs) are increasingly applied to robotic navigation; however, existing benchmarks primarily emphasize navigation success rates while paying limited attention to so…
Zero-Shot Adaptation to Robot Structural Damage via Natural Language-Informed Kinodynamics Modeling
Anuj Pokhrel, Aniket Datar, Mohammad Nazeri +2
High-performance autonomous mobile robots endure significant mechanical stress during in-the-wild operations, e.g., driving at high speeds or over rugged terrain. Although these pl…
Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionals
Puqi Zhou, Ali Asgarov, Aafiya Hussain +9
Videos from fleets of ground robots can advance public safety by providing scalable situational awareness and reducing professionals' burden. Yet little is known about how to desig…
Applying Ground Robot Fleets in Urban Search: Understanding Professionals' Operational Challenges and Design Opportunities
Puqi Zhou, Charles R. Twardy, Cynthia Lum +6
Urban searches demand rapid, defensible decisions and sustained physical effort under high cognitive and situational load. Incident commanders must plan, coordinate, and document t…
Understanding Fire Through Thermal Radiation Fields for Mobile Robots
Anton R. Wagner, Madhan Balaji Rao, Xuesu Xiao +1
Safely moving through environments affected by fire is a critical capability for autonomous mobile robots deployed in disaster response. In this work, we present a novel approach f…
Learning from Hallucinating Critical Points for Navigation in Dynamic Environments
Saad Abdul Ghani, Kameron Lee, Xuesu Xiao
Generating large and diverse obstacle datasets to learn motion planning in environments with dynamic obstacles is challenging due to the vast space of possible obstacle trajectorie…
Single-Snapshot Localization Using Sparse Extremely Large Aperture Arrays
Yunqiao Hu, Xuesu Xiao, Steven Jones +1
This paper investigates single-snapshot direction-of-arrival (DOA) estimation and target localization with coherent sparse extremely large aperture arrays (ELAAs) in automotive rad…
Towards Data-Driven Metrics for Social Robot Navigation Benchmarking
Pilar Bachiller-Burgos, Ulysses Bernardet, Luis V. Calderita +8
This paper presents a joint effort towards the development of a data-driven Social Robot Navigation metric to facilitate benchmarking and policy optimization for ground robots. We…
LLM-Enhanced Path Planning: Safe and Efficient Autonomous Navigation with Instructional Inputs
Pranav Doma, Aliasghar Arab, Xuesu Xiao
Autonomous navigation guided by natural language instructions is essential for improving human-robot interaction and enabling complex operations in dynamic environments. While larg…