Open AccessAutonomous Vehicle for Drug Delivery
Author(s) -
K Nandakumar,
Stuart Surya,
K. Karthick,
N. Raviraj,
B Cheran,
V Poovizhi,
Gokul Sridharan,
C. Nimisha
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/995/1/012037
Subject(s) - mobile robot , point cloud , computer science , global positioning system , lidar , robot , obstacle , obstacle avoidance , computer vision , simultaneous localization and mapping , artificial intelligence , mobile robot navigation , real time computing , motion planning , autonomous robot , remote sensing , robot control , geography , telecommunications , archaeology
Autonomous vehicles are intended to move in an environment without any human intervention. In order to determine the structure of the environment, we have to rely on sensors data to build the map and to localize the vehicle within its environment. This paper presents the autonomous vehicle built using 2D LIDAR and Robot Operating System(ROS). If the environment is to be explored is outdoor we can rely on GPS to track the location the autonomous vehicle, whereas in an indoor environment we cant do so. For building the map of the environment and for the vehicle’s localisation simultaneous localisation and mapping (SLAM) is used. The LIDAR data is used to find out the corresponding distance of the obstacle from the robot. Based on this point cloud data map is generated denoting the obstacle, explored area, unexplored area and the location of the robot with respect to the map. Data from the encoder is used to navigate the robot. Path planning is done using A* algorithm to find out the shortest distance between the starting and the destination point. The experimental result helped us in comparing the performance of the autonomous mobile robot built using ultrasonic sensor with the autonomous mobile robot built using LIDAR.