Physically Feasible Repair of Reactive, Linear Temporal Logic-Based, High-Level Tasks

A typical approach to creating complex robot behaviors is to compose atomic controllers, or skills, such that the resulting behavior satisfies a high-level task; however, when a task cannot be accomplished with a given set of skills, it is difficult to know how to modify the skills to make the task...

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Veröffentlicht in:IEEE transactions on robotics Jg. 39; H. 6; S. 4653 - 4670
Hauptverfasser: Pacheck, Adam, Kress-Gazit, Hadas
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.12.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Automation
Encoding
Failure analysis
Failure detection and recovery
Feasibility
formal methods in robotics and automation
Grounding
Maintenance engineering
Robotics and automation
Robots
Safety
Skills
specification repair
Symbols
Task analysis
Task complexity
task planning
Temporal logic
ISSN:1552-3098, 1941-0468
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Zusammenfassung:A typical approach to creating complex robot behaviors is to compose atomic controllers, or skills, such that the resulting behavior satisfies a high-level task; however, when a task cannot be accomplished with a given set of skills, it is difficult to know how to modify the skills to make the task possible. We present a method for combining symbolic repair with physical feasibility checking and implementation to automatically modify existing skills such that the robot can execute a previously infeasible task. We encode robot skills in linear temporal logic (LTL) formulas that capture both safety constraints and goals for reactive tasks. Furthermore, our encoding captures the full skill execution, as opposed to prior work where only the state of the world before and after the skill is executed are considered. Our repair algorithm suggests symbolic modifications, then attempts to physically implement the suggestions by modifying the original skills subject to Linear Temporal Logic (LTL) constraints derived from the symbolic repair. If skills are not physically possible, we automatically provide additional constraints for the symbolic repair. We demonstrate our approach with a Baxter and a Clearpath Jackal.
Bibliographie:ObjectType-Article-1
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ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2023.3304009