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Dynamic obstacle avoidance Algorithm for the mobile robot

LI Cai-hong1，2;LI Yi-bin1;FAN Chen1   

  1. 1. School of Control Science and Engineering，Shandong University；2. School of Computer Science and Technology，Shandong University of Technoloy，Zibo 255049，China
  • Received:2007-07-21 Revised:1900-01-01 Online:2007-10-24 Published:2007-10-24
  • Contact: LI Cai-hong

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Abstract: A new hybrid algorithm of dynamic obstacle avoidance was introduced for local path planning under an uncertainty environment. It is a combination of the rolling planning and RBF neural network (RBFNN) forecast. The moving trajectory of the dynamic obstacle was illustrated by using a camera lens, and a heart-shaped sequence was acquired from the samples. The RBFNN prediction model was built based on these data. A dynamic rolling window within the scope of the scanning ultrasonic sensor was established according to current location when the mobile robot was in real-time planning. Forecast computation was started when a rolling window into the dynamic obstacle was detected. The next moving location of the obstacle was predicted based on the three adjacent values of time sequence. Thus the dynamic obstacle avoidance issue converts into instantaneous static once and the real-time planning was reallized. This method can improve dynamic obstacle avoidance and the safety of real-time planning. Simulation results show that the method is feasible and efficient.

Key words: dynamic obstacle avoidance, dynamic rolling planning, RBFNN, forecast

CLC Number: 

  • TP242.6
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