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Volume 8 Issue 2
Feb.  2021

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Zhao Gao, Jiahu Qin, Shuai Wang and Yaonan Wang, "Boundary Gap Based Reactive Navigation in Unknown Environments," IEEE/CAA J. Autom. Sinica, vol. 8, no. 2, pp. 468-477, Feb. 2021. doi: 10.1109/JAS.2021.1003841
Citation: Zhao Gao, Jiahu Qin, Shuai Wang and Yaonan Wang, "Boundary Gap Based Reactive Navigation in Unknown Environments," IEEE/CAA J. Autom. Sinica, vol. 8, no. 2, pp. 468-477, Feb. 2021. doi: 10.1109/JAS.2021.1003841

Boundary Gap Based Reactive Navigation in Unknown Environments

doi: 10.1109/JAS.2021.1003841
Funds:  This work was supported in part by the National Natural Science Foundation of China (61922076, 61873252), and in part by the Fok Ying-Tong Education Foundation for Young Teachers in Higher Education Institutions of China (161059)
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  • Due to the requirements for mobile robots to search or rescue in unknown environments, reactive navigation which plays an essential role in these applications has attracted increasing interest. However, most existing reactive methods are vulnerable to local minima in the absence of prior knowledge about the environment. This paper aims to address the local minimum problem by employing the proposed boundary gap (BG) based reactive navigation method. Specifically, the narrowest gap extraction algorithm (NGEA) is proposed to eliminate the improper gaps. Meanwhile, we present a new concept called boundary gap which enables the robot to follow the obstacle boundary and then get rid of local minima. Moreover, in order to enhance the smoothness of generated trajectories, we take the robot dynamics into consideration by using the modified dynamic window approach (DWA). Simulation and experimental results show the superiority of our method in avoiding local minima and improving the smoothness.


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    • The narrowest gap extraction algorithm (NGEA) is proposed which extracts the narrowest gap to evaluate the accessibility reliably.
    • We present the boundary gap which is a new concept for reactive navigation, and design a strategy of identifying the boundary gap that enables the robot to move along the obstacle boundary, which can lessen the possibility of ending in local minima. To the best of our knowledge, it is the first time to employ the gap based method to tackle the local minimum problem.
    • The navigation performance in terms of the trajectory smoothness is improved by applying a modified dynamic window approach (DWA) into our framework.


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