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An Improved Path Planning Algorithm With Adaptive Parameters and Predictions
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AI
DOI：10.1109/JSYST.2023.3274187.png)
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Abstract
En 中文
An improved path planning algorithm based on dynamic window approach (DWA) is proposed to optimize real-time paths for agents moving in complex environments with plenty of static and/or dynamic obstacles, path constraints, and performance constraints. In order to improve the accuracy of the evaluation function and the adaptability of the agents to different obstacle environments, the weight of the evaluation function is ameliorated by designing adaptive laws in this article. Meanwhile, aiming at the defect of local minima in DWA algorithm, a low-speed steering strategy is presented to help the robot escape the U-shaped trap. Especially, in the case of dynamic obstacle environment, a predictive scheme is carried out for the agents to reach the destination safely by fitting the trajectory of the dynamic obstacles to calculate their possible future positions, and then setting these positions as virtual obstacles. By comparison, some simulations and experiments are illustrated to show that the proposed algorithms are superior to the DWA algorithm in terms of running time, path length, and security to a large extent.
Keywords:
Heuristic algorithms
Trajectory
Prediction algorithms
Vehicle dynamics
Optimization
Collision avoidance
Turning
Dynamic obstacles
dynamic window approach (DWA)
obstacle avoidance
path planning
trap escape
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