Active Exploitation of Redundancies in Reconfigurable Multirobot Systems

While traditional robotic systems come with a monolithic system design, reconfigurable multirobot systems can share and shift physical resources in an on-demand fashion. Multirobot operations can benefit from this flexibility by actively managing system redundancies depending on current tasks and ha...

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Bibliographic Details
Published in:IEEE transactions on robotics Vol. 38; no. 1; pp. 180 - 196
Main Author: Roehr, Thomas M.
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Exploitation
Multi-robot systems
Multiple robots
Multirobot systems
Organizations
Planning
Reasoning
reconfigurable robots
Reconfiguration
Redundancy
Robot kinematics
Robotics
Robots
scheduling and coordination
Space exploration
space robotics and automation
Systems design
Task analysis
ISSN:1552-3098, 1941-0468
Online Access:Get full text
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Summary:While traditional robotic systems come with a monolithic system design, reconfigurable multirobot systems can share and shift physical resources in an on-demand fashion. Multirobot operations can benefit from this flexibility by actively managing system redundancies depending on current tasks and having more options to respond to failure events. To support this active exploitation of redundancies in robotic systems, this article details an organization model as basis for planning with reconfigurable multirobot systems. The model allows us to exploit redundancies when optimizing a multirobot system's probability of survival with respect to a desired mission. The resulting planning approach trades safety against efficiency in robotic operations and thereby offers a new perspective and tool to design and improve multirobot missions. We use a simulated multirobot planetary exploration mission to evaluate this approach and highlight an exemplary performance landscape. Our implementation of the organization model is open-source available ( https://github.com/rock-knowledge-reasoning/knowledge-reasoning-moreorg ).
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ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2021.3118284