A Software-Defined Distributed Architecture for Controlling Unmanned Swarm Systems

Author:

An Xuyang12ORCID,Yu Xuewei123,Song Weilong12,Han Le12,Yang Tingting12,Li Zhaodong12,Su Zhibao12

Affiliation:

1. China North Artificial Intelligence & Innovation Research Institute, Beijing 100072, China

2. Collective Intelligence & Collaboration Laboratory, Beijing 100072, China

3. College of Artificial Intelligence, Nankai University, Tianjin 300350, China

Abstract

An unmanned swarm is usually composed of a group of homogeneous or heterogeneous hardware platforms, software control systems, and interfaces for human–computer interaction that operate collectively to achieve a specific goal by information interaction. They exhibit robustness and fault tolerance when facing complex missions, making it crucial in military, transportation, intelligent traffic, and other fields. However, the coupling between the hardware and software of a heterogeneous unmanned swarm can indeed have significant implications for system flexibility, software development and deployment, and hardware maintenance. Over the years, there has been a significant shift from traditional hardware-focused control systems to a greater emphasis on the core software layer. In this paper, a distributed network architecture is proposed to solve this problem, in which hardware resources are abstracted and represented to accomplish standardization and unification by defining a consistent and uniform set of data formats, and a resource pool of hardware data is constructed to realize the function that the number and scale of platforms is irrelevant, the task module can be plug-and-play at any time, and the software can be configured on demand. The resource scheduling of a single platform is achieved through process and thread communication using shared memory, while the resource scheduling of a cross platform is achieved through a network using request and response and subscription and notification. As a result, it can satisfy the development of functional modules in a software-defined mode and gradually improve the intelligence capability of an unmanned swarm. Based on the above architecture, the overall framework of the autonomous navigation system and the collaborative control system has been successfully established. Finally, a hardware-in-the-loop simulation environment is constructed, and the integration and verification of the proposed distributed architecture is carried out by the cooperative formation experiment, which proves the feasibility of this proposal.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference13 articles.

1. Parallel Learning Architecture of micROS Powering the Ability of Life-Long Autonomous Learning;Dai;J. Comput. Res. Dev.,2019

2. A player/stage system for context-aware intelligent environments;Kranz;Proc. UbiSys,2006

3. Michal, D.S., and Etzkorn, L. (2011, January 24–26). A comparison of player/stage/gazebo and microsoft robotics developer studio. Proceedings of the 49th Annual Southeast Regional Conference, Kennesaw, GA, USA.

4. Multi-robot data mapping simulation by using microsoft robotics developer studio;Barrientos;Simul. Model. Pract. Theory,2014

5. Kraetzschmar, G., Utz, H., Sablatnög, S., Enderle, S., and Palm, G. (2002). Proceedings of the RoboCup 2001: Robot Soccer World Cup V 5, Springer.

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