Document Type
Article
Keywords
Robotics, Formal Verification, Validation, Behavior-Based
Disciplines
Artificial Intelligence and Robotics | Computer Engineering | Robotics
Abstract
Abstract—Certain robot missions need to perform predictably in a physical environment that may have significant uncertainty. One approach is to leverage automatic software verification techniques to establish a performance guarantee. The addition of an environment model and uncertainty in both program and environment, however, means the state-space of a model-checking solution to the problem can be prohibitively large. An approach based on behavior-based controllers in a process-algebra framework that avoids state-space combinatorics is presented here. In this approach, verification of the robot program in the uncertain environment is reduced to a filtering problem for a Bayesian Network. Validation results are presented for the verification of a multiple-waypoint and an autonomous exploration robot mission.
Index Terms— Program Verification, Autonomous Agents, Behavior-based Systems, Control Architectures and Programming.
Publication Title
Robotics & Autonomous Systems
Volume
98
Article Number
1066
Publication Date
2017
First Page
89
Last Page
104
Language
English
Peer Reviewed
1
Recommended Citation
Damian Lyons, Ron Arkin, Shu Jiang, Matthew O'Brien, Feng Tang and Peng Tang, “Performance Verification for Robot Missions in Uncertain Environments” Robotics & Autonomous Systems 98 (2017) pp89-104.
Version
Published
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
