A path planning method and device and mobile device

Abstract

The invention provides a path planning method and device, mobile equipment and a computer readable storage medium. The path planning method includes the steps that the current environment is sampled according to an initial sampling strategy, and multiple state sample points are obtained; first value corresponding to each state sample point is obtained based on a first path planning algorithm; second value corresponding to each state sample point is obtained based on a second path planning algorithm; the weighted sum of the first value and the second value is used for obtaining value corresponding to each state sample point; and driving path planning is determined based on the value corresponding to the current state sample points. According to the embodiment of the path planning method anddevice, the mobile equipment and the computer readable storage medium, a current driving path is determined by combining the two path planning algorithms, the complex driving environment can be adapted, the gap with the control behavior of a human driver is reduced, the amount of operational data needing to be recorded can also be reduced, and thus the determined current driving path is more reasonable.

Description

technical field [0001] The present application relates to route planning technology, and in particular to a route planning method and device, a mobile device, and a computer-readable storage medium. Background technique [0002] With the development of computer technology and artificial intelligence, unmanned vehicles have become an important research direction and research hotspot in the field of robotics. The path planning and control strategy of the unmanned vehicle refers to the strategy for the unmanned vehicle to choose its own actions in various states. The actions of the unmanned vehicle include acceleration, deceleration, steering, whistle, switch lights, etc. For the path planning and control strategy of unmanned vehicles, there are currently two main types of methods, one is based on heuristic rules, and the other is based on expert demonstration. [0003] The method based on heuristic rules is to regulate the path planning and control of unmanned vehicles throu...

AI Technical Summary

Problems solved by technology

[0005] However, the method based on heuristic rules is sometimes difficult to adapt to the complex driving environment, and the path planning and control strategy obtained through the rules are far from the control behavior of human drivers.

However, the method based on expert demonstration needs to record a large amount of operation data, and consumes a lot of resources such as money and time.

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