Bezier Curve-Based Path Planning for Robust Waypoint Navigation of Unmanned Ground Vehicle

무인차량의 강인한 경유점 주행을 위한 베지어 곡선 기반 경로 계획

  • 이상훈 (한국과학기술연구원 인지로봇센터) ;
  • 전창묵 (한국과학기술연구원 인지로봇센터) ;
  • 권태범 (한국과학기술연구원 인지로봇센터) ;
  • 강성철 (한국과학기술연구원 인지로봇센터)
  • Received : 2011.02.20
  • Accepted : 2011.03.29
  • Published : 2011.05.01


This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.


Grant : 실외 환경에 강인한 도로기반 저가형 자율주행기술 개발


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