Archive for July, 2023
Situational adaptive movement prediction for firefighting squads in indoor attack
We presented our paper “Situational Adaptive Motion Prediction for Firefighting Squads in Indoor Search and Rescue” at ICRA in the Long-Term Human Motion Prediction workshop.
Firefighting is a complex but poorly automated task. To minimize ergonomic and safety risks for firefighters, robots could be used in a collaborative approach. To enable human-robot teams in firefighting, important fundamentals are still missing. Among other things, the robot must predict human movement because occlusions are ubiquitous. In this work, we propose a novel motion prediction method for firefighting squads in indoor attack. Squad paths are generated using an optimal graph-based planning approach that represents firefighter tactics. Paths are generated on a per-room basis, allowing dynamic local adaptation of paths without global replanning. The movement of individual agents is simulated using a modification of the Headed Social Force Model. We evaluate the feasibility of the pipeline using a novel dataset generated from real footage and show its computational efficiency.
Contact: Elodie Hüsing
