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Hierarchically Decentralized Heterogeneous Multi-Robot Task Allocation System

Sujeet Kashid, Ashwin D. Kumat

TL;DR

This work addresses coordinating a heterogeneous multi-robot system for ISRU-like lunar tasks using a hierarchically decentralized, auction-based MRTA framework. It integrates a MURDOCH-inspired task allocation with a three-tier robot workflow (scout for localization, excavator for digging, hauler for transport) and analyzes three bidding policies within a ROS2/pyrobosim simulation. The approach emphasizes scalability, fault tolerance, and explicit cooperation through structured communication and coalition strategies. Findings show trade-offs between speed, travel distance, and auction dynamics across policies, informing design choices for autonomous space robotics coordination.

Abstract

With plans to send humans to the Moon and further, the supply of resources like oxygen, water, fuel, etc., can be satiated by performing In-Situ Resource Utilization (ISRU), where resources from the extra-terrestrial body are extracted to be utilized. These ISRU missions can be carried out by a Multi-Robot System (MRS). In this research, a high-level auction- based Multi-Robot Task Allocation (MRTA) system is developed for coordinating tasks amongst multiple robots with distinct capabilities. A hierarchical decentralized coordination architecture is implemented in this research to allocate the tasks amongst the robots for achieving intentional cooperation in the Multi-Robot System (MRS). 3 different policies are formulated that govern how robots should act in the multiple auction situations of the auction-based task allocation system proposed in this research, and their performance is evaluated in a 2D simulation called pyrobosim using ROS2. The decentralized coordination architecture and the auction-based MRTA make the MRS highly scalable, reliable, flexible, and robust.

Hierarchically Decentralized Heterogeneous Multi-Robot Task Allocation System

TL;DR

This work addresses coordinating a heterogeneous multi-robot system for ISRU-like lunar tasks using a hierarchically decentralized, auction-based MRTA framework. It integrates a MURDOCH-inspired task allocation with a three-tier robot workflow (scout for localization, excavator for digging, hauler for transport) and analyzes three bidding policies within a ROS2/pyrobosim simulation. The approach emphasizes scalability, fault tolerance, and explicit cooperation through structured communication and coalition strategies. Findings show trade-offs between speed, travel distance, and auction dynamics across policies, informing design choices for autonomous space robotics coordination.

Abstract

With plans to send humans to the Moon and further, the supply of resources like oxygen, water, fuel, etc., can be satiated by performing In-Situ Resource Utilization (ISRU), where resources from the extra-terrestrial body are extracted to be utilized. These ISRU missions can be carried out by a Multi-Robot System (MRS). In this research, a high-level auction- based Multi-Robot Task Allocation (MRTA) system is developed for coordinating tasks amongst multiple robots with distinct capabilities. A hierarchical decentralized coordination architecture is implemented in this research to allocate the tasks amongst the robots for achieving intentional cooperation in the Multi-Robot System (MRS). 3 different policies are formulated that govern how robots should act in the multiple auction situations of the auction-based task allocation system proposed in this research, and their performance is evaluated in a 2D simulation called pyrobosim using ROS2. The decentralized coordination architecture and the auction-based MRTA make the MRS highly scalable, reliable, flexible, and robust.
Paper Structure (17 sections, 7 equations, 6 figures)

This paper contains 17 sections, 7 equations, 6 figures.

Table of Contents

  1. Introduction
  2. Problem Formulation
  3. Approach
  4. Search Strategy for scout robot
  5. Coordination Architecture
  6. Multi-Robot Task Allocation
  7. Messaging Protocol
  8. Auction Protocol
  9. Auction Announcement
  10. Self Utility Evaluation
  11. Bid submission
  12. Winner Selection
  13. Closing Auction
  14. Policy 1: First come first serve
  15. Policy 2: Anticipatory coalition formation of excavator and hauler robots
  16. ...and 2 more sections

Figures (6)

  • Figure 1: 2D simulated area
  • Figure 2: Spiralling outward search pattern
  • Figure 3: Hierarchically decentralized MRS
  • Figure 4: Time taken by each policy for goal completion
  • Figure 5: Distance traveled by each kind of robot
  • ...and 1 more figures