A Hybrid Obstacle Avoidance Method: Follow the Gap with Dynamic Window Approach

2017 ◽  
Author(s):  
Aykut Ozdemir ◽  
Volkan Sezer
Keyword(s):  
Obstacle Avoidance ◽  
Window Approach

scholarly journals Formation Control and Obstacle Avoidance Algorithm of a Multi-USV System Based on Virtual Structure and Artificial Potential Field

2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Shape Change ◽  
Artificial Potential Field ◽  
Generation Algorithm ◽  
Time Performance ◽  
Movement Ability ◽  
Window Approach ◽  
Avoidance Problem

This paper proposes a formation generation algorithm and formation obstacle avoidance strategy for multiple unmanned surface vehicles (USVs). The proposed formation generation algorithm implements an approach combining a virtual structure and artificial potential field (VSAPF), which provides a high accuracy of formation shape keeping and flexibility of formation shape change. To solve the obstacle avoidance problem of the multi-USV system, an improved dynamic window approach is applied to the formation reference point, which considers the movement ability of the USV. By applying this method, the USV formation can avoid obstacles while maintaining its shape. The combination of the virtual structure and artificial potential field has the advantage of less calculations, so that it can ensure the real-time performance of the algorithm and convenience for deployment on an actual USV. Various simulation results for a group of USVs are provided to demonstrate the effectiveness of the proposed algorithms.

Real-time Obstacle Avoidance of Hovercraft Based on Follow the Gap with Dynamic Window Approach

2018 ◽  
Author(s):  
Yuanhui Wang ◽  
Wenchao She ◽  
Mingyu Fu ◽  
Fuguang Ding ◽  
Shaoshi Dai
Keyword(s):  
Real Time ◽  
Obstacle Avoidance ◽  
Window Approach

scholarly journals Obstacle Avoidance in a Three-Dimensional Dynamic Environment Based on Fuzzy Dynamic Windows

2021 ◽  
Vol 11 (2) ◽  
pp. 504
Author(s):  
Ce Xu ◽  
Zhenbang Xu ◽  
Mingyi Xia
Keyword(s):  
Obstacle Avoidance ◽  
Three Dimensional ◽  
Dynamic Environment ◽  
Local Minima ◽  
Performance Constraints ◽  
Window Method ◽  
Planning Approach ◽  
Optimization Function ◽  
Window Approach ◽  
Reactive Method

This paper presents a real-time path planning approach for controlling the motion of space-based robots. The algorithm can plan three-dimensional trajectories for agents in a complex environment which includes numerous static and dynamic obstacles, path constraints, and/or performance constraints. This approach is extended based on the dynamic window approach (DWA). As the classic reactive method for obstacle avoidance, DWA uses an optimized function to select the best motion command. The original DWA optimization function consists of three weight terms. Changing the weights of these terms will change the behavior of the algorithm. In this paper, to improve the evaluation ability of the optimization function and the robot’s ability to adapt to the environment, a new optimization function is designed and combined with fuzzy logic to adjust the weights of each parameter of the optimization function. Given that DWA has the defect of local minima, which makes the robot hard to escape U-shaped obstacles, a dual dynamic window method and local goals are adopted in this article to help the robot escape local minima. By comparison, the proposed method is superior to traditional DWA and fuzzy DWA (F_DWA) in terms of computational efficiency, smoothness and security.

A PROVABLY CONVERGENT DYNAMIC WINDOW APPROACH TO OBSTACLE AVOIDANCE

2002 ◽  
Vol 35 (1) ◽  
pp. 115-120 ◽  
Author(s):  
Petter Ögren ◽  
Naomi E. Leonard
Keyword(s):  
Obstacle Avoidance ◽  
Window Approach

scholarly journals Path Planning for Smart Car Based on Dijkstra Algorithm and Dynamic Window Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Li-sang Liu ◽  
Jia-feng Lin ◽  
Jin-xin Yao ◽  
Dong-wei He ◽  
Ji-shi Zheng ◽  
...  
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Driving ◽  
Initial Position ◽  
Depth Information ◽  
Dijkstra Algorithm ◽  
Planning Algorithm ◽  
Local Path ◽  
Window Approach ◽  
Path Planning Algorithm

Path planning and obstacle avoidance are essential for autonomous driving cars. On the base of a self-constructed smart obstacle avoidance car, which used a LeTMC-520 depth camera and Jetson controller, this paper established a map of an unknown indoor environment based on depth information via SLAM technology. The Dijkstra algorithm is used as the global path planning algorithm and the dynamic window approach (DWA) as its local path planning algorithm, which are applied to the smart car, enabling it to successfully avoid obstacles from the planned initial position and reach the designated position. The tests on the smart car prove that the system can complete the functions of environment map establishment, path planning and navigation, and obstacle avoidance.

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