A self-guided approach for navigation in a minimalistic foraging robotic swarm

IF 3.7 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Autonomous Robots Pub Date : 2023-04-27 DOI:10.1007/s10514-023-10102-y

Steven Adams, Daniel Jarne Ornia, Manuel Mazo Jr

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引用次数: 3

Abstract

We present a biologically inspired design for swarm foraging based on ant’s pheromone deployment, where the swarm is assumed to have very restricted capabilities. The robots do not require global or relative position measurements and the swarm is fully decentralized and needs no infrastructure in place. Additionally, the system only requires one-hop communication over the robot network, we do not make any assumptions about the connectivity of the communication graph and the transmission of information and computation is scalable versus the number of agents. This is done by letting the agents in the swarm act as foragers or as guiding agents (beacons). We present experimental results computed for a swarm of Elisa-3 robots on a simulator, and show how the swarm self-organizes to solve a foraging problem over an unknown environment, converging to trajectories around the shortest path, and test the approach on a real swarm of Elisa-3 robots. At last, we discuss the limitations of such a system and propose how the foraging efficiency can be increased.

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一种用于最小觅食机器人群导航的自引导方法

我们提出了一种基于蚂蚁信息素部署的生物启发的群体觅食设计，其中群体被认为具有非常有限的能力。机器人不需要全局或相对位置测量，群体是完全分散的，不需要到位的基础设施。此外，系统只需要在机器人网络上进行一跳通信，我们没有对通信图的连通性做任何假设，并且信息和计算的传输与代理的数量相比是可扩展的。这是通过让群体中的代理充当觅食者或引导代理(信标)来实现的。我们给出了在模拟器上计算Elisa-3机器人群体的实验结果，并展示了群体如何在未知环境中自组织解决觅食问题，收敛到最短路径周围的轨迹，并在真实的Elisa-3机器人群体上测试了该方法。最后，讨论了该系统的局限性，并提出了提高觅食效率的方法。

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来源期刊

Autonomous Robots 工程技术-机器人学

CiteScore

7.90

自引率

5.70%

发文量

审稿时长

3 months

期刊介绍： Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development. The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.