Computer Science

Computer Science ›› 2019, Vol. 46 ›› Issue (4): 241-246.doi: 10.11896/j.issn.1002-137X.2019.04.038

• Artificial Intelligence • Previous Articles     Next Articles

Online Obstacle Avoidance and Path Planning of Quadrotor Oriented to Urban Environment

CHENG Hao-hao1, YANG Sen1,2, QI Xiao-hui1   

  1. Department of Unmanned Aerial Vehicle,Army Engineering University,Shijiazhuang 050003,China1
    School of Automation Science and Electrical Engineering,Beihang University,Beijing 100083,China2
  • Received:2018-03-15 Online:2019-04-15 Published:2019-04-23

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Abstract: Aiming at the online obstacle avoidance and path planning problem of quadrotor for urban environment,this paper studied the improved algorithm of rapidly-exploring random tree (RRT) and artificial potential field.In order to solve the problem of slow convergence speed and tortuous path of RRT algorithm,first,the probability guidance is used to guide the growth direction of random tree,and then the track is cut and the B-spline curve is smoothed to generate a feasible track that satisfies the performance requirements of quadrotor.In order to solve the problems that the artificial potential field method is trapped into local minimums and oscillations,the initial path is first generated by using the improved potential field function,and then the path planning is optimized by using path point clipping and B-spline curve.Finally,under the urban environment model,the improved RRT algorithm is compared with the improved artificial potential field method from the aspects of algorithm planning time,planning track length and turning angle.The results show that the improved RRT algorithm is more suitable for online obstacle avoidance and path planning of quadrotor.

Key words: Improved artificial potential field method, Improved RRT algorithm, Obstacle avoidance, Online path planning, Quadrotor

CLC Number: 

  • TP301
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