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Collaboration in Multi-Robot Systems: Taxonomy and Survey over Frameworks for Collaboration

Riwa Karam, Alexander A. Nguyen, Ruoyu Lin, David R. Martin, Diana Morales, Brooks A. Butler, Magnus Egerstedt

Abstract

Collaboration is a central theme in multi-robot systems as tasks and demands increasingly require capabilities that go beyond what any one individual robot possesses. Yet, despite extensive work on cooperative control and coordinated behaviors, the terminology surrounding collective multi-robot interaction remains inconsistent across research communities. In particular, cooperation, coordination, and collaboration are often treated interchangeably, without clearly articulating the differences among them. To address this gap, we propose definitions that distinguish and relate cooperation, coordination, and collaboration in multi-robot systems, highlighting the support of new capabilities in collaborative behaviors, and illustrate these concepts through representative examples. Building on this taxonomy, different frameworks for collaboration are reviewed, and technical challenges and promising future research directions are identified for collaborative multi-robot systems.

Collaboration in Multi-Robot Systems: Taxonomy and Survey over Frameworks for Collaboration

Abstract

Collaboration is a central theme in multi-robot systems as tasks and demands increasingly require capabilities that go beyond what any one individual robot possesses. Yet, despite extensive work on cooperative control and coordinated behaviors, the terminology surrounding collective multi-robot interaction remains inconsistent across research communities. In particular, cooperation, coordination, and collaboration are often treated interchangeably, without clearly articulating the differences among them. To address this gap, we propose definitions that distinguish and relate cooperation, coordination, and collaboration in multi-robot systems, highlighting the support of new capabilities in collaborative behaviors, and illustrate these concepts through representative examples. Building on this taxonomy, different frameworks for collaboration are reviewed, and technical challenges and promising future research directions are identified for collaborative multi-robot systems.
Paper Structure (22 sections, 4 figures, 1 table)

This paper contains 22 sections, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Taxonomy on Cooperation, Coordination, and Collaboration
  3. Background on Cooperation and Coordination
  4. Multi-Robot Collaboration
  5. Organizational Structures
  6. Centralized
  7. Decentralized
  8. Hierarchical
  9. Framework Inspirations and Tools
  10. Ecology-Inspired Frameworks
  11. Human-Swarm Interaction Frameworks
  12. Game Theoretic Frameworks
  13. Learning-Based Frameworks
  14. Comparisons
  15. Challenges and Future Research Directions
  16. ...and 7 more sections

Figures (4)

  • Figure 1: Venn diagram illustrating the relationship among cooperation, coordination, and collaboration in multi-robot systems. Cooperation serves as a superset for coordination and capability complementarity, whose intersection corresponds to collaboration.
  • Figure 2: Illustrative examples of cooperation, coordination, capability complementarity, and collaboration in a simplified warehouse environment with homogeneous robots and three different package sizes; small packages can be moved by any single robot, medium packages can be moved by any two robots, and the large package can be moved by any three robots. In all cases, robots share a common goal of moving all packages from the warehouse to a loading zone (depicted by the green area), which is the basis of cooperative "intent" between robots. Red arrows represent the task assignment of each robot (that is, which package to move) and a crossed-out red arrow represents a "bad" assignment (that is, redundant assignment or infeasible task). In (a), robots randomly, or greedily, go to move packages without regard for the selection of other robots (that is, no coordination) and without taking joint action(s) to move larger packages (that is, no capability complementarity), which can lead to suboptimal assignments and exclude all packages that require more than one robot to transport. In (b), robots share information to determine what small box each robot must move, but do not take any joint action to move packages together (that is, no capability complementarity). In (c), robots randomly, or greedily, go to move packages (that is, no coordination); however, robots may form joint capabilities, should they happen to arise, and move packages together. In (d), robots share information to determine what box size each robot must move, or what arrangements in terms of capability complementarity are needed to clear the warehouse of all box sizes.
  • Figure 3: Illustrative example of organizational structures for collaborative multi-robot systems. In (a), a central planner assigns tasks to each robot, and robots engage in collaborative actions only when directed by the controller. In (b), robots independently decide when to collaborate often through communicating requests for assistance. In (c), the robots are divided into teams with one robot acting as team leader. The leader instructs the other robots on when and how to take collaborative actions.
  • Figure 4: Example of a mutualistic interaction between two heterogeneous species, the Nile crocodile and the Egyptian plover, in nature b1961scientificmolles1999ecology. There is mutual benefit from this collaboration: the crocodile gets a free dental cleaning, preventing infections, and the bird gets a free meal.

Theorems & Definitions (4)

  • Definition 1
  • Definition 2
  • Definition 3
  • Definition 4