Publication

Abstract : Wheel-chair robotics has emerged as a promising technology with notable advancements over the years promoting mobility and enhancing the lives of people who are physically challenged. Autonomous navigation has paved the way in implementing self-driving wheelchairs with the help of lidar sensor, camera, and other different technical devices. Through our study, we conducted a thorough analysis by comparing and visualizing three distinct 2D LiDAR placement positions on a wheelchair robot called Self-E, following autonomous navigation in three different environments. By testing the self-driving wheelchair robot in diverse environments, we aimed to assess its adaptability and effectiveness across different real-world scenarios. We meticulously recorded key factors such as navigation time, collision occurrences, area coverage, and map accuracy. The robot's trajectory and environmental perception are recorded for each Lidar position. The simulations are performed using gazebo platform and the obtained maps were visualized using Rviz in Robotic Operating System (ROS ecosystem). This research provides valuable insights into optimizing LiDAR sensor placement to enhance the performance of wheelchair robots in real-world environments.