ARM Student Lead: William Hector Lindauer II Student Team Members: Leilani Alvarado, Joshua Butler, Dakota Jacobs, William Lindauer, Lauren Otto, Hunter Smith Faculty: Dr. Mehran Andalibi and Dr. Richard Mangum Embry-Riddle’s Robotics Lab is requesting the creation of a low-cost robotic arm that can interface with a robotic base and uses computer vision AI for object detection. The arm will be used as a learning tool helping students understand how to integrate two robotic systems along with how implementing AI in robotics can benefit the system. The robotic arm being developed will be able to grab objects using programmable inverse and forward kinematic operations and object detection powered by an AI assisting the robot with grabbing objects in a changing environment. The camera used will also have depth sensing allowing it to move and adjust on its own to pick up an object. Object detection will allow the robotic arm to interact with a large variety of objects, showing the versatility of AI. This robotic arm will be able to operate attached to a robotic base being developed by ODD (Octagon Differential Drive) Robot where it will be powered and able to access ODD Robot’s depth-sensing camera for additional information. In tandem with the robotic arm, a base is also being created to allow the robotic arm to be attached to the lab bench where students can continue to learn and utilize all the robotic arm’s capabilities.
ART Student Lead: Bryce Thirtyacre Student Team Members: Nicole Evenson, Emma McBride, Payton Mickelsen, Jagan Sandhu, Siddharth Shah, Bryce Thirtyacre, Madeleine Wallace Faculty: Dr. Mehran Andalibi and Dr. Richard Mangum The COE Automation Lab has commissioned ART to develop an autonomous robotic system that integrates with its existing Programmable Logic Controller (PLC) conveyor belt system. The PLC system employs an induction sensor and pneumatic actuator to sort metallic and non-metallic objects. The new system must demonstrate artificial intelligence through Computer Vision (CV) and support Python programming to align with the COE curriculum’s shift toward that language. To operate the PLC conveyor belt, the robotic system must manipulate a control panel featuring six color-coded buttons, a toggle switch, and a rotary knob without causing damage. The gripper must be capable of pressing buttons, toggling the switch between on/off positions, twisting the knob, and using a stylus to interact with the Human Machine Interface (HMI). The CV module must interpret status indicators, voltage meter readings, knob positions, and HMI screen text. It must also identify and classify objects by shape and color before grasping and placing them on the conveyor belt for material-based sorting.
14 SENIOR CAPSTONE PROJECTS | COLLEGE OF BUSINESS, SECURITY AND INTELLIGENCE
Made with FlippingBook - professional solution for displaying marketing and sales documents online