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As part of the Electrical and Computer Engineering Senior Design course, the Navigation and Controls team is designing three subsystems that are critical to achieving Level 5 autonomy (fully autonomous, no user required) for Megatron, a ground-based vehicle competing in the 2026 International Ground Vehicle Competition (IGVC) AutoNav Challenge. The subsystems are an artificial potential field planner, e-stop embedded system, and motor control embedded system. The autonomous robot detects and avoids obstacles while smoothly navigating to predefined GPS locations. Sensor data from LiDAR, GPS, and on-board camera modules will be used to generate efficient routes and regulate movement. This ensures robot stability and responsiveness via a closed loop control system. Main research topics include the development and optimization of algorithms responsible for path planning, trajectory tracking, and motion control. The creation of a needs-metrics matrix derived from customer needs kicked off the design process. These metrics translate into engineering requirements that guide the development of the navigation and control subsystem. For autonomous path planning, an artificial potential field algorithm was developed. As a safety measure, an e-stop circuit is being developed. For robot motion regulation, two proportional integral derivative (PID) motor control algorithms were implemented in simulation and then implemented and verified experimentally with a microcontroller, motor driver, and brushed direct-current motor. The Robotic Operating System 2 (ROS2) middleware is used to implement the planner and high-level e-stop and control algorithms, and embedded C is used to implement the low-level e-stop and controller logic. Key steps taken towards completion include the needs–metrics matrix, identification of measurable performance goals from the engineering requirements, and selection of planner and control algorithms. Next steps include hardware and algorithm tuning, subsystem integration and final system testing.