ZHUGE Chengchen, CAI Yunfei, TANG Zhenmin. A Novel Dynamic Obstacle Avoidance Algorithm Based on Collision Time Histogram[J]. Chinese Journal of Electronics, 2017, 26(3): 522-529. doi: 10.1049/cje.2017.01.008
Citation: ZHUGE Chengchen, CAI Yunfei, TANG Zhenmin. A Novel Dynamic Obstacle Avoidance Algorithm Based on Collision Time Histogram[J]. Chinese Journal of Electronics, 2017, 26(3): 522-529. doi: 10.1049/cje.2017.01.008

A Novel Dynamic Obstacle Avoidance Algorithm Based on Collision Time Histogram

doi: 10.1049/cje.2017.01.008
Funds:  This work is supported by the National Natural Science Foundation of China (No.61305134, No.61371040), Specialized Research Fund for the Doctoral Program of Higher Education (No.20133219120035), National Major Project of Core Electronic Devices, High-end Generic Chips and Basic Software (No.2015zx01041101), and 111 Project (No.B13022).
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  • Corresponding author: CAI Yunfei (corresponding author) was born in 1983. He received the Ph.D. degree from Nanjing University of Science and Technology. His current research interests are multi-robots architecture, probabilistic robotics and multi-robots SLAM. (Email:cyf@njust.edu.cn)
  • Received Date: 2015-12-09
  • Rev Recd Date: 2016-06-02
  • Publish Date: 2017-05-10
  • Robot path planning in uncertain dynamic environment is a hot issue in the field of Unmanned ground vehicle (UGV). Starting from the practical demands of UGV, we propose a novel dynamic obstacle avoidance algorithm based on Collision time histogram (CTH). Given current steering angle, an effective collision check model, which is called Collision check circles (CCC), is firstly calculated. The local environment information is then combined with CCC to generate the proposed CTH. The nonholonomic nature of the vehicle is embedded in this process. Finally, the proposed algorithm calculates the executing steering angle by considering both the CTH and the target point. Extensive experiments and comparisons are conducted to evaluate the performance of the proposed algorithm. Simulation experiments are firstly conducted to verify its feasibility. Furthermore, real-world experiment is conducted to verify its effectiveness. Experimental results demonstrate the practical value of the proposed algorithm.
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