Driverless smart car automatic collision avoidance method based on quantum wolf pack algorithm

A wolf pack algorithm, unmanned technology, applied in two-dimensional position/channel control and other directions

Active Publication Date: 2019-11-19
HARBIN ENG UNIV
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AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of path planning and obstacle avoidance strategy for unmanned intelligent vehicles in low-speed environm...

Method used

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  • Driverless smart car automatic collision avoidance method based on quantum wolf pack algorithm
  • Driverless smart car automatic collision avoidance method based on quantum wolf pack algorithm
  • Driverless smart car automatic collision avoidance method based on quantum wolf pack algorithm

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Embodiment Construction

[0024] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings, but it is not limited thereto. Any modification or equivalent replacement of the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention should be covered by the present invention. within the scope of protection.

[0025] The invention provides an automatic collision avoidance method for unmanned intelligent vehicles based on the quantum wolf pack algorithm, such as Figure 9 As shown, the method includes the following steps:

[0026] Step 1. Use environmental sensors to scan the surrounding environment of the smart car within a certain distance (the experimental platform is built within about 10 meters), and use the obstacle sensor data processed by the multi-sensor data fusion algorithm to establish the environment through the Gmapping open source algorithm pack...

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Abstract

The invention discloses a driverless smart car automatic collision avoidance method based on a quantum wolf pack algorithm. The method is based on global path planning and monitors the surrounding environment of the driverless car in real time during the safe driving process of the smart car, and in the case of a dynamic or static obstacle, with the shortest target path as an objective function, the quantum wolf pack algorithm is optimized to obtain a destination arrival path with the shortest local collision avoidance; and the optimal steering angle of the local driverless smart car and the angle of restoring the original path are determined to obtain a local path planning result of the driverless smart car. Global path planning and local path planning are combined to be applied to driverless driving of the smart car, driving of the smart car can be planned on the whole globally, the road condition information can be judged in real time during the driving process through local path planning, the real-time path is changed timely, the driverless smart car is thus ensured to arrive at the destination quickly and steadily, and the safety and the reliability of driverless driving can be improved.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence and relates to an automatic collision avoidance method for an intelligent vehicle based on a quantum wolf pack algorithm. Background technique [0002] Unmanned intelligent vehicles are also called intelligent wheeled mobile robots. Theoretically, it is interpreted as a kind of robot system that can perceive the surrounding environment and the state of the vehicle itself in a certain way, and can realize the autonomous movement towards the set goal while driving on the road section with obstacles or other environments, and then complete the set operation function. . So far, the unmanned intelligent vehicle system has achieved surprising results and foresighted experience through the efforts of scientific researchers and the development of long-term research and experiments. In an environment that can be determined in advance, research related to intelligent vehicle navigation and...

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/02
Inventor 刘洪丹刘胜张兰勇丁一轩李冰李芃孙玥
Owner HARBIN ENG UNIV
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