CN211827022U

CN211827022U - Binocular vision aided driving system based on FPGA

Info

Publication number: CN211827022U
Application number: CN201922486384.3U
Authority: CN
Inventors: 刘星; 尚广利; 张伟; 胡斌
Original assignee: Suzhou Tsingtech Microvision Electronic Technology Co ltd
Current assignee: Suzhou Tsingtech Microvision Electronic Technology Co ltd
Priority date: 2019-12-31
Filing date: 2019-12-31
Publication date: 2020-10-30
Anticipated expiration: 2029-12-31

Abstract

The utility model discloses a two mesh vision aided driving systems based on FPGA, which comprises a housin, be provided with FPGA main chip in the casing, FPGA main chip embeds there is degree of depth study neural network, two mesh cameras are connected to FPGA main chip, two mesh cameras set up in vehicle windshield's middle part, wireless communication module, GPS module and voice module are still connected to FPGA main chip, two mesh cameras include a FPGA chip, two cameras are connected at the both ends of FPGA chip. Based on binocular camera, can improve the precision of range finding greatly, binocular camera structure is simple, the angle of regulation camera that can be convenient.

Description

Binocular vision aided driving system based on FPGA

Technical Field

The utility model relates to a driver fatigue detects technical field, specifically relates to a binocular vision aided driving system based on FPGA.

Background

With the popularity of automobile driving, more and more people choose to drive automobiles. The advanced driving auxiliary system senses the surrounding environment at any time in the driving process of the automobile by using various sensors installed on the automobile, collects data, identifies, detects and tracks static and dynamic objects, and performs systematic operation and analysis by combining with map data of a navigator, so that a driver can be made to perceive possible dangers in advance, the comfort and the safety of automobile driving are effectively improved, and the occurrence of traffic accidents is reduced. The advanced driving assistance system on the market at present has the disadvantages of complex structure, inconvenient use and poor performance. Moreover, the monocular camera is mostly installed on the basis of the vehicle body, has the inherent physical defect of low distance measurement precision, and has poor recognition capability of pedestrians and special-shaped objects. The current binocular camera has the disadvantages of complex structure, inconvenient installation and high cost.

A driving assistance system of utility model patent with publication number CN 209290277U includes a vehicle body; the binocular camera is arranged at the rear end of the vehicle body; the image processing module is connected with the binocular camera; and the display module is connected with the image processing module. The utility model discloses an acquire the image at automobile body rear through two mesh cameras. The structure of a binocular camera is not disclosed, and the driving assistance system is only used for displaying the images and the actual distance value of the obstacle in the images from the vehicle body on the display module at the same time, so that driving assistance in other aspects cannot be performed.

SUMMERY OF THE UTILITY MODEL

In order to solve the technical problem, the utility model provides a binocular vision aided driving system based on FPGA based on two mesh cameras, can improve the precision of range finding greatly, two mesh cameras are simple structure, the angle of regulation camera that can be convenient.

The utility model adopts the technical proposal that:

the utility model provides a binocular vision aided driving system based on FPGA, includes the casing, be provided with FPGA main chip in the casing, FPGA main chip embeds there is degree of depth study neural network, two mesh cameras are connected to FPGA main chip, two mesh cameras set up in vehicle windshield's middle part, wireless communication module, GPS module and voice module are still connected to FPGA main chip, two cameras are connected to two mesh cameras including a FPGA chip, two cameras are connected at the both ends of FPGA chip.

In an optimal technical scheme, the binocular camera further comprises an arm processing chip connected with the FPGA chip, and the arm processing chip is provided with a GPU module.

In a preferred technical scheme, an RJ45 network port, a URAT serial port module, a TF card acquisition module and a USB debugging module are arranged outside the shell, and the RJ45 network port, the URAT serial port module, the TF card acquisition module and the USB debugging module are connected with the FPGA main chip.

In the preferred technical scheme, the binocular camera includes upper cover, lower cover, and sets up the FPGA chip between upper cover and lower cover, the lower cover both ends are provided with the camera installation cavity, the periphery of the outer end camera installation cavity of lower cover is provided with the recess, the FPGA chip is fixed in the lower cover through adjusting device, adjusting device is including setting up installing support and the fixed bolster at both ends in the lower cover, the installing support sets up the pivot mounting hole, the upper end of installing support is provided with the tooth's socket mounting hole, the tooth's socket mounting hole is used for installing the tooth's socket in the pivot mounting hole, the tooth's socket distributes on rotatory path, one side upper end of fixed bolster is provided with the gag lever post, and the opposite side is provided with the pivot, the outer end of pivot is provided with the barb, the pivot is installed in the pivot mounting hole, barb and tooth's.

Compared with the prior art, the beneficial effects of the utility model are that:

1. the utility model discloses a supplementary driving system is based on two mesh cameras, ensures the exactness of surrounding environment perception, and the precision of range finding can be improved greatly to the reliability, can effectual realization to the detection of pedestrian, barrier, and is more accurate.

2. The binocular camera has a simple structure, and the angle of the camera can be conveniently adjusted.

Drawings

The invention will be further described with reference to the following drawings and examples:

FIG. 1 is a schematic block diagram of a binocular vision aided driving system based on an FPGA;

FIG. 2 is a schematic interface diagram of the system of the present invention;

fig. 3 is a schematic overall structure diagram of a binocular camera;

fig. 4 is an exploded view of a binocular camera.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the description is intended to be illustrative only and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.

Examples

As shown in fig. 1, the utility model discloses a two mesh vision aided driving systems based on FPGA, including the casing, be provided with FPGA main chip in the casing, FPGA main chip embeds there is degree of depth study neural network, and two mesh cameras are connected to FPGA main chip, two mesh cameras set up in vehicle windshield's middle part, and wireless communication module, GPS module and voice module are still connected to FPGA main chip, and two cameras are connected to two mesh cameras including a FPGA chip, FPGA chip's both ends.

And the binocular camera is used for perceiving the surrounding environment, generating a real-time depth parallax map and reconstructing three-dimensional of the surrounding environment.

The GPS/Beidou positioning module is used for positioning the current place through GPS equipment, acquiring longitude and latitude information of the equipment and displaying position information in a map.

The wireless communication module is a 4G communication module and transmits the driving assisting information to the network platform through a 4G network.

The voice module is a loudspeaker, and the output is a control instruction after the target is deeply learned and recognized.

And the deep learning neural network is used for detecting and identifying the target by the depth parallax map and the original image.

The interface schematic diagram of the binocular vision aided driving system is shown in fig. 2. The system comprises: the system comprises an RJ45 network port connected with an FPGA main chip, a URAT serial port module, a TF card acquisition module and a USB debugging module.

The binocular camera adopts two cameras and an FPGA or an arm processing chip with GPU acceleration for 1 block, and realizes the real-time output of depth information.

The structural schematic diagrams of the binocular camera are shown in fig. 3 and 4, and the length, the width and the height of the camera assembly are 185mm, 43mm and 58mm respectively; wherein, the distance of two cameras is 120 mm. The mounting position is generally the right middle position of the vehicle windshield, and the ground clearance is between 1.5m and 2.4 m.

The binocular camera comprises an upper cover 5, a lower cover 1 and an FPGA chip 3 arranged between the upper cover 5 and the lower cover 1, two cameras 11 are arranged at two ends of the FPGA chip 3, camera mounting cavities 12 are arranged at two ends of the lower cover 1, a groove 13 is arranged at the periphery of the outer end camera mounting cavity 12 of the lower cover 1, the FPGA chip 3 is fixed in the lower cover 1 through an adjusting device, the adjusting device comprises a mounting bracket 10 and a fixing bracket 20 which are arranged at two ends in the lower cover 1, the mounting bracket 10 is provided with a rotating shaft mounting hole 14, a tooth socket mounting hole (not shown in the figure) is arranged at the upper end of the mounting bracket 10, the tooth socket mounting hole is used for mounting a tooth socket 15 in the rotating shaft mounting hole 14, the tooth socket 15 can be fixedly mounted through a screw, the tooth socket 15 is distributed on a rotating path, a limiting rod 21 is arranged at the upper end of one side of the fixing bracket 20, the limiting, the outer end of the rotating shaft 22 is provided with a barb, the rotating shaft 22 is arranged in the rotating shaft mounting hole 14, and the barb is matched with the tooth groove. The angle of regulation camera that this regulation structure can be convenient, the periphery of camera installation cavity is provided with the recess for the angle that the camera was adjusted is bigger.

The deep learning neural network selects a trained multitask cascade convolution neural network, and carries out real-time environmental feature extraction on the depth parallax map through the network, wherein the extracted features mainly comprise edge contour information, parallax map depth information and target color information, and pedestrians and obstacles are identified.

It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.

Claims

1. The utility model provides a binocular vision aided driving system based on FPGA, its characterized in that, includes the casing, be provided with FPGA main chip in the casing, FPGA main chip embeds there is the degree of depth study neural network, two mesh cameras are connected to FPGA main chip, two mesh cameras set up in vehicle windshield's middle part, wireless communication module, GPS module and voice module are still connected to FPGA main chip, two mesh cameras include a FPGA chip, two cameras are connected at the both ends of FPGA chip.

2. The binocular vision aided driving system based on the FPGA of claim 1, wherein the binocular camera further comprises an arm processing chip connected with the FPGA chip, the arm processing chip being provided with a GPU module.

3. The binocular vision aided driving system based on the FPGA according to claim 1, wherein an RJ45 net port, a URAT serial port module, a TF card acquisition module and a USB debugging module are arranged outside the shell, and the RJ45 net port, the URAT serial port module, the TF card acquisition module and the USB debugging module are connected with an FPGA main chip.

4. The binocular vision aided driving system based on the FPGA according to claim 1, wherein the binocular camera comprises an upper cover, a lower cover and an FPGA chip arranged between the upper cover and the lower cover, camera mounting cavities are arranged at two ends of the lower cover, a groove is arranged at the periphery of the outer end camera mounting cavity of the lower cover, the FPGA chip is fixed in the lower cover through an adjusting device, the adjusting device comprises a mounting bracket and a fixing bracket which are arranged at two ends in the lower cover, the mounting bracket is provided with a rotating shaft mounting hole, a tooth socket mounting hole is arranged at the upper end of the mounting bracket, the tooth socket mounting hole is used for mounting a tooth socket in a rotating shaft mounting hole, the tooth socket is distributed on a rotating path, a limiting rod is arranged at the upper end of one side of the fixing bracket, a rotating shaft is arranged at the other side of the fixing bracket, a barb is arranged at the outer end of the rotating shaft, and, the barb is matched with the tooth groove.