Probabilistic Verification of Multi-robot Missions in Uncertain Environments

• Published in: 2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI) pp. 56 - 63
• Main Authors: Lyons, Damian M., Arkin, Ronald C., Shu Jiang, Harrington, Dagan, Feng Tang, Peng Tang
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01-11-2015
• Subjects: Artificial intelligence; Autonomous; Behavior-Based Robots; Computer programs; Expert systems; Geometry; Missions; Multi-robot Missions; Multiple robots; Probabilistic logic; Probabilistic Verification; Program verification (computers); Robot kinematics; Robot sensing systems; Robots; Software; Uncertainty; Validation
• ISSN: 1082-3409; 2375-0197
• DOI: 10.1109/ICTAI.2015.22

The effective use of autonomous robot teams in highly-critical missions depends on being able to establish performance guarantees. However, establishing a guarantee for the behavior of an autonomous robot operating in an uncertain environment with obstacles is a challenging problem. This paper addresses the challenges involved in building a software tool for verifying the behavior of a multi-robot waypoint mission that includes uncertain environment geometry as well as uncertainty in robot motion. One contribution of this paper is an approach to the problem of a-priori specification of uncertain environments for robot program verification. A second contribution is a novel method to extend the Bayesian Network formulation to reason about random variables with different subpopulations, introduced to address the challenge of representing the effects of multiple sensory histories when verifying a robot mission. The third contribution is experimental validation results presented to show the effectiveness of this approach on a two-robot, bounding overwatch mission.