Alex Goldhoorn

Publication

← Back to Publications

Searching and Tracking People with Cooperative Mobile Robots

Alex Goldhoorn, Anaïs Garrell, René Alquézar and Alberto Sanfeliu
Autonomous Robots, vol. 42, pp. 1-25, 2017
PDF | BibTeX | DOI

Abstract

Social robots should be able to search and track people in order to help them. In this paper we present two different techniques of coordinated multi-robots for searching and tracking people. A probability map (belief) of a target person location is maintained, and to initialize and update it, two methods were implemented and tested: one based on a reinforcement learning algorithm and the other based on a particle filter. The person is tracked if visible, otherwise an exploration is done by making a balance, for each candidate location, between the belief, the distance, and whether close locations are already being explored by other robots of the team. The validation of the approach was accomplished throughout an extensive set of simulations using up to five agents and a large amount of dynamic obstacles; furthermore, over three hours of real-life experiments with two robots searching and tracking were recorded and analysed.

Experimental Videos

Videos demonstrating the experiments done with the Multi-agent HB-PF Explorer to find and follow people. The robot searches and follows a person recognized using AR Markers.

Video Legend

Each experiment video shows three sections:

Map Elements

Probability Map Elements

Experiment Statistics

Summary of over 3 hours of real-life experiments with two robots:

Metric Exploration Search & Track Tracking Total
Distance per robot (km) 1.2 1.2 0.7 3.2
Total time (h) 1.1 1.2 0.9 3.2
Avg. visibility (%) 0 16.3 36.4 15.3
Avg. distance to person (m) - 8.4 ± 6.4 8.4 ± 5.6 8.3 ± 5.9
Avg. time found (s) - 106.8 ± 138.7 23.5 ± 42.5 72.9 ± 117.6

More Information

For detailed videos and additional experiment information, please refer to the full page with embedded videos.

Additional materials: Map information

← Back to Publications