Abstract

In this new era of smart sensors, the field of robotics has enormously grown to its next level, the automation process in the industrial sector increases the fast product development as well as cost reduction and the manpower requirement can be decreased. In industries, autonomous mapping and navigating robot will play a vital role for the large warehouse where multiple task can be implemented and done using the autonomous navigating general-purpose robot, in this project an autonomous navigating robot is developed based on the lidar system using SLAM methodology which has the ability to map the environment on its own and able to find the shortest / convenient path to the destination, this robot uses the lidar as a input sensor based on the input taken it creates a map and finds the path for navigation even in the partially observable environment, This robot model uses the model based reflex agent as its environment and uses the HECTOR SLAM (simultaneous localization and mapping) along with adaptive Monte Carlo localization (AMCL) on a robot operating system (ROS) platform deployed on Raspberry Pi, using the combination of HECTOR SLAM and AMCL both the dynamic and static environment can be handled by the robot due to the adaptiveness of the robot this is highly reliable for the use in the industrial environment, HECTOR SLAM technique eliminates the requirement of odometry as this HECTOR SLAM takes the lidar position as a feedback system unlike other SLAM algorithms. This work also features the implementation of both A* algorithm and AMCL based on the use cases and the user preference. By giving an add-on device to this robot which can accomplish the task given by the user like transportation of products and cleaning the floor of the industries, security and surveillance and much more activities. This kind of robot helps to reduce the manpower required in the industrial sector and to automate the industrial sector which paves the way for the next generation of development in the industry.KeywordsHECTOR SLAMLidarROSAGVPath findingAutomation

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