This week, our team completed the interim demo, successfully demonstrating the full workflow of voice activation, gesture-triggered motor control, and ToF-based obstacle avoidance. Based on feedback from the TA and professor, we identified several improvements: switching the activation gesture from Thumbs Up to Thumbs Down to reduce unintentional triggers, and increasing the ToF obstacle detection threshold to give the robot more time to decelerate. I also began researching the follow-user logic, which will use the hand’s pixel x-coordinate to determine the user’s lateral position and the stereo depth value to estimate distance, allowing the robot to steer toward the user rather than moving in a fixed direction. To handle depth noise, I plan to average readings across consecutive frames.
For verification, I am planning tests for both of my subsystems. For gesture detection, I will test recognition accuracy across varying distances, lighting levels, and hand orientations, targeting at least 90 percent accuracy over 50 trials per condition, along with measuring detection latency. For the ToF subsystem, I will compare sensor readings against known distances and test whether the robot correctly chooses the appropriate avoidance direction when obstacles are detected. Next week, I will focus on implementing the follow-user navigation logic and mounting the ToF sensors onto the chassis.