AgungHari / Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-AvoidanceView external linksLinks
Detection is performed by combining two approaches: Yolo bounding box and pose landmarks, where both outputs are mapped into a 10x10 grid (made with OpenCV), which serves as a reference for the wheelchair to avoid obstacles. Commands are sent from the NUC to the ESP32, which then moves the motor.
☆27Apr 18, 2025Updated 9 months ago
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