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 (5 months ago)

Commits 54 (last one about a month ago)

Stargazers 26 (0 this week)

Watchers 2 (0 this week)

Forks 3

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RepositoryStats indexes 595,856 repositories, of these AgungHari/Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-Avoidance is ranked #585,288 (2nd percentile) for total stargazers, and #485,301 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #117,048/119,431.

AgungHari/Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-Avoidance is also tagged with popular topics, for these it's ranked: pose-estimation (#325/329)

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yolov8 grid10x10 kursiroda mediapipe bounding-box pose-estimation wheelchair-control

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54 commits on the default branch (main) since jan '22

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updated: 2024-12-20 @ 05:30am, id: 831498068 / R_kgDOMY-nVA