Robot Guided Evacuation with Viewpoint Constraints

TL;DR

This paper introduces a viewpoint-based non-linear MPC algorithm for evacuation guiding robots, enabling them to effectively lead humans to safety while maintaining line-of-sight, demonstrated through simulations and real-world UAV experiments.

Contribution

The paper proposes a novel MPC algorithm that incorporates environment layout and viewpoint constraints for evacuation robots, improving guidance effectiveness.

Findings

Increased visibility of UAV to humans during evacuation.

Faster evacuation times achieved with the proposed method.

Effective guidance demonstrated in both simulated and real environments.

Abstract

We present a viewpoint-based non-linear Model Predictive Control (MPC) for evacuation guiding robots. Specifically, the proposed MPC algorithm enables evacuation guiding robots to track and guide cooperative human targets in emergency scenarios. Our algorithm accounts for the environment layout as well as distances between the robot and human target and distance to the goal location. A key challenge for evacuation guiding robot is the trade-off between its planned motion for leading the target toward a goal position and staying in the target's viewpoint while maintaining line-of-sight for guiding. We illustrate the effectiveness of our proposed evacuation guiding algorithm in both simulated and real-world environments with an Unmanned Aerial Vehicle (UAV) guiding a human. Our results suggest that using the contextual information from the environment for motion planning, increases the visibility of the guiding UAV to the human while achieving faster total evacuation time.