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Dispensing medicine in hospital wards is a mechanized process, but it is difficult to develop on a large scale due to the uncertainty of the environment. In this study, a customized dispenser robot was designed to automatically deliver drugs to the designated ward according to the given instructions. The Visual identity module (OpenMV) is designed to collect images from the progress and then compare them with pre-stored images to achieve automatic pathfinding. Among them, the tracking part uses PID open-loop operation to increase the accuracy of movement. The ward number enables the camera to recognize the number in different scenes for many times, which increases the accuracy of recognition. The unique structure of this study provides an innovative and effective way to customize ward dispensing.

With STM32 as the control core, the new guide cap has ranging obstacle avoidance, ranging obstacle avoidance, intelligent recognition, voice interaction, GPS positioning and other functions. The system uses OpenMV4 Cam H7 Plus intelligent camera for continuous real-time monitoring and effective feedback of traffic lights, zebra crossings and other important road information; Assisted by ultrasonic sensor, the electrical signal is converted into ultrasonic output through the transmitter to effectively measure the distance of obstacles; At the same time, the user's location information is sent to the surrounding vehicles and passers-by in real time through the Wi-Fi module and GPS positioning, ensuring the user's safety to the greatest extent.

No abstract

When there is no elevator at the station and airport or the elevator is crowded, the ramp of baggage checking is steep, the weight of luggage package is too heavy, it takes time and effort, and it is very easy to knock against and cause damage to the contents of the package.Our climbing robot carries out autonomous navigation based on visual SLAM. Equipped with ROS robot operating system, it adopts laser SLAM mapping navigation technology and tracks as running parts, which is suitable for various terrains. The adoption of binocular vision, can be more accurate analysis of the surrounding environment. The robot is equipped with MPU9250 attitude sensor, which is convenient for solving robot attitude. Jetson Nano was used as the upper computer and STM32F429 as the lower computer.