A Versatile Vision-Pheromone-Communication Platform for Swarm Robotics

Liu, Tian, Sun, Xuelong, Hu, Cheng , Fu, Qinbing and Yue, Shigang (2021) A Versatile Vision-Pheromone-Communication Platform for Swarm Robotics. In: 2021 IEEE International Conference on Robotics and Automation (ICRA), 30 May-5 June 2021, Xi'an, China.

Full content URL: https://doi.org/10.1109/ICRA48506.2021.9561911

A Versatile Vision-Pheromone-Communication Platform for Swarm Robotics
Authors' Accepted Manuscript
ICRA21_A Versatile Vision-Pheromone-Communication Platform for Swarm Robotics.pdf - Whole Document

Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


This paper describes a versatile platform for swarm robotics research. It integrates multiple pheromone communication with a dynamic visual scene along with real time data transmission and localization of multiple-robots. The platform has been built for inquiries into social insect behavior and bio-robotics. By introducing a new research scheme to coordinate olfactory and visual cues, it not only complements current swarm robotics platforms which focus only on pheromone communications by adding visual interaction, but also may fill an important gap in closing the loop from bio-robotics to neuroscience. We have built a controllable dynamic visual environment based on our previously developed ColCOS$\Phi$ (a multi-pheromones platform) by enclosing the arena with LED panels and interacting with the micro mobile robots with a visual sensor. In addition, a wireless communication system has been developed to allow transmission of real-time bi-directional data between multiple micro robot agents and a PC host. A case study combining concepts from the internet of vehicles (IoV) and insect-vision inspired model has been undertaken to verify the applicability of the presented platform, and to investigate how complex scenarios can be facilitated by making use of this platform.

Keywords:vision, pheromones, Micro Robot, Robotics platforms
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:47322
Deposited On:19 Nov 2021 10:50

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