Degree of Contribution

Lead

Document Type

Conference Proceeding

Keywords

Robotics, Formal Verification, Validation, Behavior-Based

Disciplines

Artificial Intelligence and Robotics | Computer Engineering | Robotics

Abstract

Abstract— Localization and mapping algorithms can allow a robot to navigate well in an unknown environment. However, whether such algorithms enhance any specific robot mission is currently a matter for empirical validation. In this paper we apply our MissionLab/VIPARS mission design and verification approach to an autonomous robot mission that uses probabilistic localization software.

Two approaches to modeling probabilistic localization for verification are presented: a high-level approach, and a sample-based approach which allows run-time code to be embedded in verification. Verification and experimental validation results are presented for two different missions, each using each method, demonstrating the accuracy of verification, and both are compared with verification of an odometry-only mission, to show the mission-specific benefit of localization.

Publication Title

IEEE International Conference on Tools with AI, Nov 2016 San Jose CA

Article Number

1068

Publication Date

11-2016

Language

English

Peer Reviewed

1

Version

Published

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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