Multi-Agent Testbed Integrated with Indoor Vision-Based Positioning System
Ramona Devi · Research Square · 2023
Abstract This paper presents a multi-agent testbed equipped with an indoor vision-based positioning system designed for the control and localization of a fleet of ground robots. This positioning system relies on overhead cameras that detect AprilTags affixed to the top of each ground robot. These cameras are connected to Raspberry Pi microcontrollers, which communicate the position information to the ground agents through a Wi-Fi network. This system provides each ground agent with accurate position information, akin to an indoor GPS system, facilitating indoor formation control and multi-agent communication. The implementation of this system is demonstrated using NVIDIA's JetBot as the ground vehicle, equipped with a Jetson Nano microcontroller. I employ PID control techniques to implement formation control, and all agents and cameras communicate through the Robotic Operating System (ROS). The AprilTag library in Python is utilized for the detection and extraction of information from AprilTags.