Robot autonomous logistics transportation navigation method based on neural network
A neural network and navigation method technology, applied in the field of robot transportation and navigation, to achieve the effect of reducing requirements, real-time performance and low continuity of actions
Pending Publication Date: 2022-01-21
SUZHOU UNIV
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Problems solved by technology
[0008] The purpose of this application is to address the deficiencies of the above-mentioned prior art, aiming to solve the autonomous navigation problem of mobile robots in logistics and transportation scenarios from the perspective of artificial intelligence, that is, to provide a method for autonomous logistics and transportation navigation of robots based on neural networks
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Embodiment 1
[0052] Embodiment 1, a neural network-based robot autonomous logistics transportation navigation method, comprising the following steps:
[0053] Step 1: The simulation platform built is used to simulate the real scene, which includes mobile robots and obstacles.
[0054] Among them, for mobile robots, laser sensors, radar positioning devices and gyroscopes are mounted on mobile robots. Such as figure 1 The 17 rays shown represent 17 laser beams, figure 1 Arrows point in the direction of the end point.
[0055] Among them, for obstacles, such as figure 2 As shown in , a number of black lines and squares (in essence, other methods can also be used) are used to represent the random combination of obstacles to form a maze-like indoor scene, simulating the narrow and tortuous L-shaped scene that often appears in the storage environment.
[0056] The second step: collect human data, let the human subjects choose the moving posture of the robot in different environments by tapp...
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The invention discloses a robot autonomous logistics transportation navigation method based on a neural network, and belongs to the field of robot navigation control, and the robot autonomous logistics transportation navigation method is characterized by comprising the following steps that a plurality of laser sensors, a radar positioning device and a gyroscope are carried on a robot; wherein the laser sensor is used for detecting distribution of front obstacles; the radar positioning device and the gyroscope are respectively used for judging the end point direction and the running direction of the robot, and the difference between the end point direction and the running direction is expressed as the relative advancing direction of the robot; a plurality of black lines and square blocks are used for representing obstacles to be randomly combined to form an indoor scene similar to a labyrinth, and a scene of a real storage environment is simulated. According to the robot autonomous logistics transportation navigation method based on the neural network, compared with a traditional navigation algorithm, an environment model does not need to be established, the trained neural network is similar to a human brain, corresponding decisions are made according to perceived information, and the robot autonomous logistics transportation navigation method is completely capable of coping with emergency situations.
Description
technical field [0001] The present application relates to the field of robot transportation navigation, and more specifically, relates to a neural network-based autonomous logistics transportation navigation method for robots. Background technique [0002] The autonomous navigation of robots in the logistics industry requires that the robot be able to independently reach the destination from the starting point without colliding with any obstacles during the movement. [0003] Related research such as: [0004] CN113240331A discloses a full-range intelligent logistics robot system, which includes a robot automatic driving system, a user pick-up and delivery system, a server and a logistics cabinet system. Transfer to the pick-up location specified by the user pick-up and mail system; the server is used for information interaction between the user pick-up and mail system and the robot automatic driving system. [0005] CN107436610A discloses a vehicle and robot carrying navi...
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IPC IPC(8): G01C21/20G01C21/34G01S13/06G06N3/04G06N3/08
CPCG01C21/20G01C21/343G01S13/06G06N3/04G06N3/084Y02T10/40
Inventor 陈逸阳贺海东程传鑫
Owner SUZHOU UNIV