Behavior-Tree-Based Person Search for Symbiotic Autonomous Mobile Robot Tasks
Abstract
We consider the problem of people search by a mobile social robot in case of a situation that cannot be solved by the robot alone. Examples are physically opening a closed door or operating an elevator. Based on the Behavior Tree framework, we create a modular and easily extendable action sequence with the goal of finding a person to assist the robot. By decomposing the Behavior Tree as a Discrete Time Markov Chain, we obtain an estimate of the probability and rate of success of the options for action, especially where the robot should wait or search for people.In a real-world experiment, the presented method is compared with other common approaches in a total of 588 test runs over the course of one week, starting at two different locations in a university building. We show our method to be superior to other approaches in terms of success rate and duration until a finding person and returning to the start location.
Cite
@article{arxiv.2103.09162,
title = {Behavior-Tree-Based Person Search for Symbiotic Autonomous Mobile Robot Tasks},
author = {Marvin Stuede and Timo Lerche and Martin Alexander Petersen and Svenja Spindeldreier},
journal= {arXiv preprint arXiv:2103.09162},
year = {2022}
}
Comments
Accepted for publication at ICRA 2021