Digital twinning of surveillance robot

Abstract

Surveillance robots provide troops with real-time information about their surroundings, including enemy positions, terrain, and potential threats. This information is invaluable for making informed decisions and ensuring the safety of military personnel. Geo-fenced robots are robots equipped with technology that restricts their movements within predefined geographic boundaries. These boundaries are typically established using GPS or other location-based technologies. In applications like the military, geo-fencing can be used to establish secure zones. Geo-fencing helps prevent robots from entering hazardous areas, reducing the risk of damage to the robot and potential harm to friendly forces or civilians This project aims at Digital twinning of robots by creating a virtual replica or model of a physical robot in a digital environment. Digital twinning allows engineers and designers to simulate and test the robot’s behavior, performance, and capabilities in a virtual environment before building the physical robot. This can lead to increased efficiency, reduced downtime, and cost savings. In this project, LiDAR (Light Detection and Ranging) sensor data is integrated with a digital twinned robot to create a virtual reproduction of the robot and its surroundings. LiDAR is a remote sensing technology that maps the robot’s surroundings in fine detail using 3D point clouds by measuring distances using laser pulses. Here we make use of RPLIDAR A1 M8 and acquire data from it using ROS with the help of a RaspberryPi4B Controller. Simulink is used to create a 3D model of the robot’s environment and the robot itself. Reinforcement learning and pure pursuit algorithms are used for developing them. This project discusses the need for geofenced autonomous robots and emphasizes the security and reliability it brings to military applications.