Reliable distribution of computational load in robot teams

Modern multi-robot systems often need to solve computationally intensive tasks but operate with limited compute resources and in the presence of failures. Cooperating to share computational tasks between robots at the edge reduces execution time. We introduce and evaluate a new computation load mana...

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Bibliographic Details
Published in:Autonomous robots 2021-03, Vol.45 (3), p.351-369
Main Authors: Valkov, Ivan, Trinder, Phil, Chechina, Natalia
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Imaging
Control
Engineering
Failure
Mechatronics
Multiple robots
Pattern Recognition and Graphics
Performance evaluation
Robotics
Robotics and Automation
Robots
Route planning
Stress concentration
Vision
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Summary:Modern multi-robot systems often need to solve computationally intensive tasks but operate with limited compute resources and in the presence of failures. Cooperating to share computational tasks between robots at the edge reduces execution time. We introduce and evaluate a new computation load management technology for teams of robots: Reliable Autonomous Mobile Programs (RAMPs). RAMPs use information about the computational resources available in the team and a cost model to decide where to execute. RAMPs are implemented in ROS on a collection of Raspberry Pi-based robots. The performance of RAMPs is evaluated using route planning, a typical computationally-intensive robotics application. A systematic study of RAMPs demonstrates a high likelihood of optimal or near-optimal distribution and hence efficient resource utilisation. RAMPs successfully complete in the presence of simultaneous, or successive, robot failures and network failures, while preserving near-optimal distribution.
ISSN:0929-5593
1573-7527
DOI:10.1007/s10514-021-09967-8