Corner Detection with 2-D RPLIDAR to Detect Furniture on TCIFFRC Tracks

Abstract

Trinity College International Firefighting Robot Contest (TCIFFRC) is a firefighting robot competition organized by Trinity College, United States. In the TCIFFRC track, there are four types of room with different characteristics. When the game starts, the robot can be located in any room with randomly placed tube-shaped obstacles (simulating furniture). The robot must be able to detect those obstacles in order to know its position, so that the robot can go out of the room avoiding the obstacles quickly. The focus of this research is to improve the ability of the robot by using corner detection to detect the furniture correctly so that the robot can know the position of the furniture. The robot in this research is a quadruped robot that has been equipped with a 2-dimensional (2-D) laser range scanner (RPLIDAR A1M8). The experiment results showed that the robot was able to detect the furniture up to 5 meters away with an error of 12.5% and 6.12% for the measured angle and the measured distance, respectively. The success rate of the robot achieved 94.7% in being able to escape from the given room with the furniture.