Multi-Robot Pickup and Delivery via Distributed Resource Allocation

In this article, we consider a large-scale instance of the classical pickup-and-delivery vehicle routing problem that must be solved by a network of mobile cooperating robots. Robots must self-coordinate and self-allocate a set of pickup/delivery tasks while minimizing a given cost figure. This resu...

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Bibliographic Details
Published in:IEEE transactions on robotics Vol. 39; no. 2; pp. 1 - 13
Main Authors: Camisa, Andrea, Testa, Andrea, Notarstefano, Giuseppe
Format: Journal Article
Language:English
Published: New York IEEE 01.04.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Cooperating robots
Costs
distributed optimization
distributed robot systems
Heuristic algorithms
Mixed integer
Multiple robots
Optimization
planning
Resource allocation
Robot kinematics
Robots
Route planning
scheduling and coordination
Task analysis
Vehicle dynamics
Vehicle routing
ISSN:1552-3098, 1941-0468
Online Access:Get full text
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Summary:In this article, we consider a large-scale instance of the classical pickup-and-delivery vehicle routing problem that must be solved by a network of mobile cooperating robots. Robots must self-coordinate and self-allocate a set of pickup/delivery tasks while minimizing a given cost figure. This results in a large, challenging mixed-integer linear problem that must be cooperatively solved without a central coordinator. We propose a distributed algorithm based on a primal decomposition approach that provides a feasible solution to the problem in finite time. An interesting feature of the proposed scheme is that each robot computes only its own block of solution, thereby preserving privacy of sensible information. The algorithm also exhibits attractive scalability properties that guarantee solvability of the problem even in large networks. To the best of our knowledge, this is the first attempt to provide a scalable distributed solution to the problem. The algorithm is first tested through Gazebo simulations on a ROS 2 platform, highlighting the effectiveness of the proposed solution. Finally, experiments on a real testbed with a team of ground and aerial robots are provided.
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ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2022.3216801