Design and Development of Smart Multipurpose Automated Guided Vehicle Implemented with SLAM and AMCL

In this present era, where technological and strategical advancement in the field of automation and smart sensors, the role of robotics plays a vital act through its actions, the process of automation in industrial sector extends its limit in rapid product development as well as cost reduction. In industries, multipurpose autonomous robot which could be able to map the environment and navigate to the desired location will play an enormous role in the large industries and in warehouse where multiple tasks to be executed and accomplished. In this work, a multipurpose autonomous ground vehicle is developed based on the SLAM algorithms using a 360º LIDAR, which could map the environment in which it is deployed and uses the same for planning a path to navigate to its desired destination. This robot uses LIDAR and camera as a major source of input parameter for determining its environment to create a map and plan a path for navigation which gives the ability to operate in both static and dynamic environment. This robot is mainly featuring with the Hector simultaneous localization and mapping (SLAM) which eliminated the need of odometry and uses its laser data as a feedback for determining the environment and to localize the state of the robot in the environment. This robot utilizes the feature of adaptive Monte Carlo localization (AMCL) for its navigation, which is programmed on a robot operating system (ROS) deployed on a Raspberry Pi. By including various features and add-on devices, robot can accomplish the task given by the user such as transportation of products, cleaning the floor and maintenance, surveillance, and much more activities using various featured programs, this robot helps in the reduction of the manpower requirement, maintenance, cost, and improve the productivity by increasing the production rate and automate the industrial sector for the current and the future generation requirements.