For my Junior Design project, I collaborated with a multidisciplinary team to design, build, and test an autonomous robotic system for the IEEE SoutheastCon 2025 Competition. The competition scenario simulated a resource collection mission in which the robot had to navigate a structured field, identify AprilTags for localization, and distinguish between two astral materials, Nebulite (non-magnetic) and Geodinium (magnetic). Points were awarded based on the robot’s ability to accurately sort these materials into the correct containers, transport bins to designated locations, and interact with a beacon, all under a strict three-minute time constraint. The scoring system emphasized both precision and efficiency, driving our design toward reliability, speed, and robust control.

The final design combined advanced sensing, mechanical, and electrical subsystems into a cohesive autonomous platform. A tracked propulsion system driven by brushless DC motors provided stability and maneuverability, while a robotic arm equipped with a two-finger adaptive gripper enabled material collection and placement. Material differentiation was achieved using a Hall Effect sensor for magnetic detection, complemented by a Pixy2 vision camera for AprilTag recognition and ultrasonic proximity sensors for obstacle avoidance. A buck/boost power regulation system and lithium-ion batteries ensured stable operation within the 30V safety limit, while the overall platform met competition requirements to fit within a 12” × 12” × 12” cube and weigh less than 12 kilograms. Safety was integral to the design, including an emergency stop mechanism and rigorous adherence to IEEE and ISO robotics safety standards.

Performance validation relied on a structured testing process. Each subsystem: motors, sensors, gripper mechanisms, and power distribution was first tested individually against engineering specifications. Integration testing followed, where subsystems and full system autonomy was evaluated through iterative trial runs under simulated competition conditions. This approach revealed timing and sequencing challenges between sensing and actuation, which were resolved through refinements in closed-loop control and software logic. By the final phase, the robot demonstrated consistent success in detecting, sorting, and delivering materials within the allotted time frame.

This project was a comprehensive application of engineering principles, spanning CAD modeling, finite element analysis, embedded programming, electronics, and system integration. It also highlighted the importance of design iteration, data-driven testing, and cross-disciplinary teamwork in delivering a competitive robotic system. Beyond meeting the technical requirements, the experience reinforced my ability to approach complex engineering problems with precision, adaptability, and innovation.