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Smart Obstacle Avoidance Using a Danger Index for a Dynamic Environment

1
School of Control Science and Engineering, Shandong University, Jinan 250061, China
2
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300131, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(8), 1589; https://doi.org/10.3390/app9081589
Received: 1 April 2019 / Revised: 12 April 2019 / Accepted: 12 April 2019 / Published: 17 April 2019
(This article belongs to the Special Issue Mobile Robots Navigation)
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PDF [7358 KB, uploaded 17 April 2019]
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Abstract

The artificial potential field approach provides a simple and effective motion planner for robot navigation. However, the traditional artificial potential field approach in practice can have a local minimum problem, i.e., the attractive force from the target position is in the balance with the repulsive force from the obstacle, such that the robot cannot escape from this situation and reach the target. Moreover, the moving object detection and avoidance is still a challenging problem with the current artificial potential field method. In this paper, we present an improved version of the artificial potential field method, which uses a dynamic window approach to solve the local minimum problem and define a danger index in the speed field for moving object avoidance. The new danger index considers not only the relative distance between the robot and the obstacle, but also the relative velocity according to the motion of the moving objects. In this way, the robot can find an optimized path to avoid local minimum and moving obstacles, which is proved by our experimental results. View Full-Text
Keywords: artificial potential field; path planning; obstacle avoidance; dynamic window; danger index artificial potential field; path planning; obstacle avoidance; dynamic window; danger index
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Sun, J.; Liu, G.; Tian, G.; Zhang, J. Smart Obstacle Avoidance Using a Danger Index for a Dynamic Environment. Appl. Sci. 2019, 9, 1589.

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