CN-122020575-A - Self-adaptive green belt trimming system based on multi-sensor fusion

CN122020575ACN 122020575 ACN122020575 ACN 122020575ACN-122020575-A

Abstract

The invention relates to the technical field of green belt pruning. The invention relates to a multi-sensor fusion-based adaptive green belt pruning system. The system comprises a sensor screening module, a region dividing module, an environment data fusion module, a model checking module and a trimming plan making module, wherein the sensor screening module is used for acquiring the geographic position of a green belt to be trimmed and screening out a temperature sensor and an image sensor with detection ranges overlapping with the geographic position, the region dividing module is used for collecting multi-period image data, combining the geographic position to construct a three-dimensional simulation model and dividing exposure and shielding regions, the environment data fusion module is used for accurately supplementing parameters such as green plants, illumination and temperature to the corresponding spatial positions of the model to form a dynamic model with morphological characteristics and growth characteristics, and the model checking module is used for realizing self-adaptive adjustment of model parameters through the analysis of the difference rate of a predicted image and an actual image, so that the simulation model is always highly matched with the actual growth state of the green plants.

Inventors

XIE YANGYANG
CHI YONGZHOU
XU HUASONG
LI XIAOPING
LI ZHAOCHENG

Assignees

武汉市汉福专用车有限公司

Dates

Publication Date: 20260512
Application Date: 20260415

Claims (9)

1. The self-adaptive green belt pruning system based on multi-sensor fusion is characterized by comprising a sensor screening module, an area dividing module, an environment data fusion module, a model checking module and a pruning plan making module: The sensor screening module acquires the geographic position of the green belt to be trimmed, and screens out a temperature sensor and an image sensor with detection ranges overlapping the geographic position; The regional division module acquires green plants, acquires image data of different time periods according to the image sensor, establishes a blank model according to the geographic position, inputs the image data of different time periods to perform green belt simulation model conversion, acquires volume data according to the green belt simulation model, and divides an exposed image region and a shielding image region; the environment data fusion module extracts illumination data of different time periods according to the image data, acquires temperature data of different time periods through a temperature sensor, and supplements green plants, the temperature data and the illumination data to a green belt simulation model; The model verification module carries out growth prediction simulation through the supplemented green belt simulation model to obtain predicted image data, verifies the predicted image data in the same period by combining the image data acquired by the image sensor, and adjusts the green belt simulation model according to a verification result; The pruning plan making module is used for setting a pruning target form, simulating the growth state of the shielding image area through the adjusted green belt simulation model, generating a green belt complete model by combining the exposed image area, and generating a pruning plan according to the green belt complete model and the pruning target form.
2. The adaptive green belt pruning system based on multi-sensor fusion of claim 1, wherein the sensor screening module is used for acquiring the geographic position of a green belt to be built at a green belt management end by establishing communication connection with the green belt management end; Searching peripheral sensors according to the geographic positions, acquiring a sensor list, acquiring detection ranges of the sensors, and performing spatial overlapping screening on the detection ranges of the sensors and the geographic positions of the green belts; When the detection range is spatially overlapped with the geographic position of the green belt, the sensor is stored; otherwise, when the detection range does not have spatial overlapping with the geographical position of the green belt, eliminating the sensor; among them, the sensor types include a temperature sensor and an image sensor.
3. The adaptive green belt pruning system based on multi-sensor fusion according to claim 2, wherein in the area dividing module, green plants corresponding to the green belt are obtained at a green belt management end; Acquiring planting time of a green belt at a green belt management end, combining the planting time with real-time to serve as a time range, dividing a plurality of time periods in the time range, and simultaneously combining the time periods with the screened image sensors to acquire image data corresponding to different time periods to form image data sets of different time periods; And establishing a blank model according to the geographic position, substituting image data sets of different time periods into the blank model, completing mapping and restoration of textures, outlines and space forms, and converting the blank model into a green belt simulation model.
4. The adaptive green belt trimming system based on multi-sensor fusion of claim 3, wherein the green belt is subjected to space measurement and calculation according to the green belt simulation model, and volume data corresponding to the green belts in different time periods are obtained according to measurement and calculation results; Combining the image data and the volume data corresponding to each time period, and dividing the region in the green belt simulation model according to the image acquisition definition and the green plant space shielding condition to divide an exposed image region and a shielding image region; The exposed image area is clear, and green plant shielding is avoided; the occlusion image area is image blurring and green plant occlusion exists.
5. The adaptive green belt pruning system based on multi-sensor fusion of claim 1, wherein in the environmental data fusion module, illumination analysis is performed on the green belt according to image data of different time periods to obtain illumination data of the green belt of different time periods; Acquiring temperature data of green belts at different time periods according to a temperature sensor; And carrying out data matching on the illumination data and the temperature data according to the time periods, correlating the illumination data and the temperature data in the same time period, combining the correlated illumination data and the temperature data with green plants of the green belt, and supplementing the green plants to the corresponding spatial positions of the green belt simulation model.
6. The adaptive green belt pruning system based on multi-sensor fusion according to claim 1, wherein the model verification module invokes a growth simulation algorithm based on the supplemented green belt simulation model to complete the natural growth state simulation of the green belt by combining the inherent growth characteristics of the green plants; And predicting the growth state of the green belt in a random selected period by a growth prediction algorithm to generate predicted image data of the green belt in the period, and then extracting the image data of the same period from the screened image sensor according to the selected period.
7. The adaptive green belt pruning system based on multi-sensor fusion of claim 6, wherein a difference threshold is set in the model verification module; extracting image data in the same time period, and combining the image data with the predicted image data to perform difference rate analysis to obtain an image difference rate; then, comparing the difference rate with a difference threshold; when the difference rate is larger than the difference threshold, adjusting the growth parameters and the environmental parameters of the green belt simulation model; And otherwise, when the difference rate is smaller than the difference threshold value, keeping the parameters of the green belt simulation model unchanged.
8. The adaptive green belt pruning system based on multi-sensor fusion according to claim 1, wherein in the pruning planning module, a pruning target form is set through a green belt management end; According to the green belt simulation model after parameter adjustment, a growth simulation algorithm is called to simulate the green planting growth state of the shielding image area divided in the latest time period, the green planting growth state of the shielding image area is obtained, and then the green belt model corresponding to the shielding image area is determined by combining the illumination data, the temperature data, the green planting species and the growth state of the adjacent exposed area of the shielding image area; And performing space splicing and fusion on the green belt model of the determined shielding image area and the exposed image area in the green belt simulation model, and performing edge optimization, space complementation and morphological calibration on the spliced and fused model to form a complete green belt model.
9. The adaptive green belt pruning system based on multi-sensor fusion according to claim 1, wherein in the pruning planning module, spatial difference analysis is performed on the green belt complete model and the pruning target form to obtain spatial difference data of the green belt complete model and the pruning target form; Acquiring the operation capacity of the pruning equipment, then carrying out pruning plan analysis by combining the space difference data with the growth tolerance of green plants and the operation capacity of the pruning equipment, determining the optimal pruning parameters from the analysis result, and generating a pruning plan of the green belt; And converting the pruning plan into an executable pruning operation instruction, and sending the executable pruning operation instruction to pruning execution equipment, wherein the control equipment prunes the green belt according to the operation instruction.

Description

Self-adaptive green belt trimming system based on multi-sensor fusion Technical Field The invention relates to the technical field of green belt pruning, in particular to a multi-sensor fusion-based self-adaptive green belt pruning system. Background In the landscaping maintenance work, green belt pruning is a core link, and the existing pruning technology comprises manual pruning, semi-automatic vehicle-mounted pruning equipment, a simple sensor-assisted pruning device and the like, and has the effects of maintaining the regular and attractive form of the green belt, guaranteeing the transparent driving vision of municipal roads and highways and adjusting the green planting growth situation so as to promote the healthy and luxuriant situation of the green planting. In the existing green belt pruning technology, manual pruning depends on experience judgment of operators, the consistency of pruning height and amplitude is poor, labor intensity is high, operation efficiency is low, the rapid maintenance requirement of a large-area green belt is difficult to meet, semi-automatic vehicle-mounted pruning equipment adopts a one-cutter pruning mode with preset fixed parameters, the growth characteristics of different green plants cannot be distinguished, the pruning strategy cannot be adjusted according to the real-time growth state of the green plants, the problem that excessive pruning damages the green plant root system or the landscaping effect is influenced due to insufficient pruning is extremely easily caused, and in order to reduce the situation, a self-adaptive green belt pruning system based on multi-sensor fusion is provided. Disclosure of Invention The invention aims to provide a multi-sensor fusion-based adaptive green belt pruning system so as to solve the problems in the background art. In order to achieve the above purpose, the self-adaptive green belt pruning system based on multi-sensor fusion is provided, and comprises a sensor screening module, a region dividing module, an environment data fusion module, a model checking module and a pruning plan making module: The sensor screening module acquires the geographic position of the green belt to be trimmed, and screens out a temperature sensor and an image sensor with detection ranges overlapping the geographic position; The regional division module acquires green plants, acquires image data of different time periods according to the image sensor, establishes a blank model according to the geographic position, inputs the image data of different time periods to perform green belt simulation model conversion, acquires volume data according to the green belt simulation model, and divides an exposed image region and a shielding image region; the environment data fusion module extracts illumination data of different time periods according to the image data, acquires temperature data of different time periods through a temperature sensor, and supplements green plants, the temperature data and the illumination data to a green belt simulation model; The model verification module carries out growth prediction simulation through the supplemented green belt simulation model to obtain predicted image data, verifies the predicted image data in the same period by combining the image data acquired by the image sensor, and adjusts the green belt simulation model according to a verification result; The pruning plan making module is used for setting a pruning target form, simulating the growth state of the shielding image area through the adjusted green belt simulation model, generating a green belt complete model by combining the exposed image area, and generating a pruning plan according to the green belt complete model and the pruning target form. As a further improvement of the technical scheme, in the sensor screening module, the geographical position of the green belt to be built is obtained at the green belt management end by establishing communication connection with the green belt management end; Searching peripheral sensors according to the geographic positions, acquiring a sensor list, acquiring detection ranges of the sensors, and performing spatial overlapping screening on the detection ranges of the sensors and the geographic positions of the green belts; When the detection range is spatially overlapped with the geographic position of the green belt, the sensor is stored; otherwise, when the detection range does not have spatial overlapping with the geographical position of the green belt, eliminating the sensor; among them, the sensor types include a temperature sensor and an image sensor. As a further improvement of the technical scheme, in the area dividing module, green plants corresponding to the green belts are obtained at the green belt management end; Acquiring planting time of a green belt at a green belt management end, combining the planting time with real-time to serve as a time range, dividing a plurality of time periods in the time range,