Table of Contents
Fetching ...

Robot Guided Evacuation with Viewpoint Constraints

Gong Chen, Malika Meghjani, Marcel Bartholomeus Prasetyo

TL;DR

The proposed MPC algorithm enables evacuation guiding robots to track and guide cooperative human targets in emergency scenarios by using the contextual information from the environment for motion planning, which increases the visibility of the guiding UAV to the human while achieving faster total evacuation time.

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.

Robot Guided Evacuation with Viewpoint Constraints

TL;DR

The proposed MPC algorithm enables evacuation guiding robots to track and guide cooperative human targets in emergency scenarios by using the contextual information from the environment for motion planning, which increases the visibility of the guiding UAV to the human while achieving faster total evacuation time.

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.
Paper Structure (4 sections, 6 equations, 3 figures)

This paper contains 4 sections, 6 equations, 3 figures.

Figures (3)

  • Figure 1: UAV guiding a human follower in a L-shaped Corridor
  • Figure 2: Example of agent guiding a human toward a goal
  • Figure 3: Example with occluded target's view while turning.