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With the rise in need of school security we hope to develop a robot that can combat this problem. The autonomous security robot at American Heritage School will be able to recognize known faces, use the RFID scanner to collect information, recognize license plates, and store and locate the data gathered from the RFID scanner and other systems. The security robot will  have a customized introductory greeting, name recognition, and schedule locator. A mounting system was designed for the cameras that can be repositioned and adjusted to best capture the license plate. The drivetrain is composed of two sets of six pneumatic wheels. Each set of wheels is powered by a custom built, dual motor, single speed gearbox. The gearboxes use a gear ratio of 21.21:1, allowing the robot to reach a top speed of roughly 7.57 feet per second.

This intern project furthered HPCC Systems integration with the robotics project by using the HPCC Systems GNN bundle with TensorFlow. Using a database with student information this project has be able to train a model to recognize known faces. This project also included upgrading the ROBOT API to work with the newest versions of ROS.


In this Video Recording, Jack provides a tour and explanation of his poster content.


Click on the poster for a larger image. The original PDF version can be found here. (Available for download).