DART: Diversity-enhanced Autonomy in Robot Teams

Author:

Ayanian Nora1ORCID

Affiliation:

1. University of Southern California, USA

Abstract

This paper defines the research area of Diversity-enhanced Autonomy in Robot Teams (DART), a novel paradigm for the creation and design of policies for multi-robot coordination. Although current approaches to multi-robot coordination have been successful in structured, well-understood environments, they have not been successful in unstructured, uncertain environments, such as disaster response. Although robot hardware has advanced significantly in the past decade, the way we solve multi-robot problems has not. Even with significant advances in the field of multi-robot systems, the same problem-solving paradigm has remained: assumptions are made to simplify the problem, and a solution is optimized for those assumptions and deployed to the entire team. This results in brittle solutions that prove incapable if the original assumptions are invalidated. This paper introduces a new multi-robot problem-solving paradigm which uses a diverse set of control policies that work together synergistically within the same team of robots. Such an approach will make multi-robot systems more robust in unstructured and uncertain environments, such as in disaster response, environmental monitoring, and military applications, and allow multi-robot systems to extend beyond the highly structured and highly controlled environments where they are successful today.

Publisher

SAGE Publications

Subject

Applied Mathematics,Artificial Intelligence,Electrical and Electronic Engineering,Mechanical Engineering,Modeling and Simulation,Software

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Cooperative Control for Air-Ground Systems via Bidirectional Signal Connection in Complex Environment;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2024-09

2. Heterogeneous Teams;Encyclopedia of Robotics;2024

3. Congestion and Scalability in Robot Swarms: A Study on Collective Decision Making;2023 International Symposium on Multi-Robot and Multi-Agent Systems (MRS);2023-12-04

4. Measuring Human-Robot Team Benefits Under Time Pressure in a Virtual Reality Testbed;2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2023-10-01

5. METHOD OF ROUTING A GROUP OF MOBILE ROBOTS IN A FIXED NETWORK FOR SEARCHING THE MISSING OBJECTS IN A TECHNOLOGICAL DISASTER ZONE;Radio Electronics, Computer Science, Control;2023-02-27

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