Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionals
Year: 2026
Type: conference-paper
Abstract: 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 design and integrate multi-robot videos into public safety workflows. Collaborating with six police agencies, we examined how such videos could be made practical. In Study 1, we present the first testbed for multi-robot ground video sensemaking. The testbed includes 38 events of interest relevant to public safety, a dataset of 20 robot patrol videos (10 day/night pairs) covering EoI types, and 6 design requirements aimed at improving current video sensemaking practices. In Study 2, we built MRVS, a tool that augments multi-robot patrol video streams with a prompt-engineered video understanding model. Participants reported reduced manual workload and greater confidence with LLM-based explanations, while noting concerns about false alarms and privacy. We conclude with implications for designing future multi-robot video sensemaking tools.
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Award: G3438899976
OpenAlex ID: W7128544288
