Official website: https://yunbum.github.io/
As [Self Driving robot Engineer] I made fully hand-made metal Self Driving RC car.
- HW setting: id, rate, type...
- SW setting: config file selection, detection range, vision ROI...
- Main Controller: Latte panda(Window or Ubuntu), Raspberry pi
- Sub Contoller: Arduino > motor, light, LED dot matrix control
- IMU (AHRS): Heading direction check
- Lidar: Emergency stop, collision avoidance
- Camera: Lane detection, Machine Learning (Object detection)
- Speaker: Connection beep, Alarm, Music(wav)
- Light: 12 LED for light / mode check, night driving test
- GNSS: RTK fixed or float mode setting (RTCM message) using NTRIP client
- NTRIP client: u-center, Lefebure
- Base Station: gnss.eseoul.go.kr, vrs3.ngii.go.kr
- Map: Google satellite, Bing..
- AHRS Heading Kalman Filter
- Image process: Binary conversion, ROI setting, Clamp, Area calculation
- interface: PoE, USB with camera file (genicam)
- Data processing: 3D, 2D raw data gathering, Clustering
- Comm: TCP/IP, UDP, Com depend on manufacture
- Range set: detectin range set > horizontal, vertical
- Display info: distance gap, degree gap, time, Latitude, Longitude,...
- Mode select: joystick
- Custom: Add any personal message or customized display text
- Function: connection alarm, Music,
- Steering: pure pursuit and PID control
- PID: minimize the angle difference between waypoint and agv-lookahead point
- GPX format: Using GPX route editor to create, modify the route easily.
- Basic: Lookahead point, Target position, Heading value > minimize degree gab(waypoint vs AGV-lookahead deg)
- Tools: Using GPX route editor, easy to make and modify waypoint for driving
- Coordination: WGS84 to TM transform
- replay the logfile after driving.
- waypoint / actual driving route compare
- statistics: distance error max/min/average
- control value check: PID, stop point etc check..
- Model: I'm testing DQN logic to apply driving algorism