Applying Ground Robot Fleets in Urban Search: Understanding Professionals' Operational Challenges and Design Opportunities

TL;DR

This study explores how ground robot fleets can support urban search operations by addressing operational challenges faced by professionals, highlighting design opportunities for effective integration.

Contribution

It provides empirical insights from focus groups with police officers on integrating ground robots into urban search, identifying key challenges and design requirements.

Findings

Robots can reduce reliance on paper references and mental calculations.

Ground robots help maintain group and situational awareness.

Design opportunities include scalable planning interfaces and real-time replanning.

Abstract

Urban searches demand rapid, defensible decisions and sustained physical effort under high cognitive and situational load. Incident commanders must plan, coordinate, and document time-critical operations, while field searchers execute evolving tasks in uncertain environments. With recent advances in technology, ground-robot fleets paired with computer-vision-based situational awareness and LLM-powered interfaces offer the potential to ease these operational burdens. However, no dedicated studies have examined how public safety professionals perceive such technologies or envision their integration into existing practices, risking building technically sophisticated yet impractical solutions. To address this gap, we conducted focus-group sessions with eight police officers across five local departments in Virginia. Our findings show that ground robots could reduce professionals' reliance on paper references, mental calculations, and ad-hoc coordination, alleviating cognitive and physical strain in four key challenge areas: (1) partitioning the workforce across multiple search hypotheses, (2) retaining group awareness and situational awareness, (3) building route planning that fits the lost-person profile, and (4) managing cognitive and physical fatigue under uncertainty. We further identify four design opportunities and requirements for future ground-robot fleet integration in public-safety operations: (1) scalable multi-robot planning and control interfaces, (2) agency-specific route optimization, (3) real-time replanning informed by debrief updates, and (4) vision-assisted cueing that preserves operational trust while reducing cognitive workload. We conclude with design implications for deployable, accountable, and human-centered urban-search support systems