Design of Mecannum Wheel-based Intelligent Stacking AGV Using Kalman Filtering Algorithm

An intelligent stacking AGV (Automated Guided Vehicle) is proposes for the intelligent handling and stacking requirements of smart factories. The AGV achieves positioning and navigation through a TOF laser ranging sensor and a gyro sensor, where the TOF laser ranging sensor is used to measure distance values and the gyro sensor is used to obtain yaw angle values. In order to achieve the accuracy and real-time of robot laser global positioning, this paper proposes a method based on the combination of Kalman filter and incremental PID algorithm, so that the robot can predict the robot position recursively through the distance information measured by TOF laser rangefinder, which effectively improves the accuracy of robot positioning and realizes the global positioning of stacking robot. The experiments and simulations were conducted on this intelligent stacking AGV. The experimental and simulation results verify the stability and reliability of the AGV in both dynamic and static environments, enabling accurate and fast completion of material stacking operations. This enables the intelligent stacking AGV to meet the requirements of high efficiency, high accuracy, and high reliability in smart factories.