AgungHari / Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-Avoidance

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.

Date Created 2024-07-20 (7 months ago)
Commits 54 (last one 3 months ago)
Stargazers 27 (0 this week)
Watchers 1 (0 this week)
Forks 3
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RepositoryStats indexes 618,350 repositories, of these AgungHari/Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-Avoidance is ranked #602,194 (3rd percentile) for total stargazers, and #558,147 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #121,410/125,168.

AgungHari/Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-Avoidance is also tagged with popular topics, for these it's ranked: pose-estimation (#333/339)

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updated: 2025-02-01 @ 02:05pm, id: 831498068 / R_kgDOMY-nVA