This week in order to make the robot to move more freely without being restricted by charging cables, we switched to using wireless power supply, then full integration testing was conducted on the system and identified several issues: the OAK-D camera repeatedly dropping and reconnecting with XLink communication errors, and unstable ToF serial data reads. And all the above issues were identified and resolved. Firstly, to make the system become more stable, we switched to a power bank instead of batteries. Then to solve the problem of the oak-d camera, I helped replace stereo depth with RGB-based distance estimation. Due to power constraints, running all three camera streams simultaneously — RGB plus both stereo monochrome cameras — placed too much demand on USB bandwidth and power, causing frequent system crashes. The depth estimation approach was reworked to derive hand distance from RGB pixel data alone, using the apparent size of the hand in the frame to estimate real-world distance by a linear lookup table on multiple reference distances. Then to adjust the estimation to make it more accurate, I performed several actual measurements (the number of pixels occupied by the hand, as well as the actual distance), and the data in the table was adjusted accordingly to make the estimates more accurate. This method also removes the short-range limitation inherent to stereo depth sensing, effectively increasing the usable hand detection range.