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Simultaneous Navigator for Autonomous Identification and Localization Robot

In this paper we present a robot system which is named SNAIL Bot. It uses a 2D 360-degree LiDAR sensor to scan the surrounding area and wheel encoders to calculate the robot's position and generate odometry data. Using this data, the robot can scan the region and the obstacles around it and transverse through them. Thus, the SNAIL bot moves autonomously in the environment.To process the data and visualize it, Raspberry Pi is used as the system, and Arduino board is used as the controller board for the motors. Odometry algorithms are used to calculate the position and movement of the bot. URDF modelling is done for the development of the bot structure. Several studies have been carried out to test the efficacy of the system developed for mapping unknown environments and obstacle avoidance. Various SLAM algorithms such as Hector SLAM and Gmapping SLAM are used for developing the grid and extracting the laser scan data. The reaction to sudden changes in the environment, robustness, and sudden commands provided to the robot were all investigated in different slam methods. Various path panning algorithms were also examined. It was found that for small indoor environments, particle filter-based algorithms were best for mapping and pose estimation and for path planning, the least cost methods were fast.