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Title: Real-time dynamic path planning of mobile robots : a novel hybrid heuristic optimization algorithm
Authors: Wu, Q
Chen, ZY
Wang, L
Lin, H
Jiang, ZJ
Li, S 
Chen, DC
Issue Date: 2019
Source: Sensors, 28 Dec. 2019, v. 20, no. 1, 188, p. 1-18
Abstract: Mobile robots are becoming more and more widely used in industry and life, so the navigation of robots in dynamic environments has become an urgent problem to be solved. Dynamic path planning has, therefore, received more attention. This paper proposes a real-time dynamic path planning method for mobile robots that can avoid both static and dynamic obstacles. The proposed intelligent optimization method can not only get a better path but also has outstanding advantages in planning time. The algorithm used in the proposed method is a hybrid algorithm based on the beetle antennae search (BAS) algorithm and the artificial potential field (APF) algorithm, termed the BAS-APF method. By establishing a potential field, the convergence speed is accelerated, and the defect that the APF is easily trapped in the local minimum value is also avoided. At the same time, by setting a security scope to make the path closer to the available path in the real environment, the effectiveness and superiority of the proposed method are verified through simulative results.
Keywords: Hybrid optimization algorithm
Mobile robot
Real-time path planning
Dynamic obstacle avoidance
Beetle antennae search algorithm (BAS)
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sensors 
EISSN: 1424-8220
DOI: 10.3390/s20010188
Rights: ©2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
The following publication Wu, Q.; Chen, Z.; Wang, L.; Lin, H.; Jiang, Z.; Li, S.; Chen, D. Real-Time Dynamic Path Planning of Mobile Robots: A Novel Hybrid Heuristic Optimization Algorithm. Sensors 2020, 20, 188, 1-18 is available at
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