阅读说明：本技术 基于声波反射能量的草地识别方法 (Grassland identification method based on sound wave reflection energy ) 是由 刘瑜 于 2020-05-02 设计创作，主要内容包括：公开一种基于声波反射能量的草地识别方法,包括运动平台,以及设置在内部的处理器,所述的运动平台底部安装超声波发射模块和超声波接收模块,并连接所述的处理器,所述的处理器内部设置草地识别算法,包括以下步骤：(1)所述的处理器每隔固定时间,发射超声波,所述的处理器在超声波信号发射之后间隔Δt时间,将所述的超声波接收模块输出信号经过AD采样,转换为数字采样信号f(n)；当采样时间达到ΔT以后,结束采样过程,此时n=N；(2)计算采样信号f(n)之和∑F=<Image he="135" wi="159" file="439572DEST_PATH_IMAGE002.GIF" imgContent="drawing" imgFormat="GIF" orientation="portrait" inline="no"></Image>；(3)如果∑F<K,则判断为草地；否则,则判断为非草地。(The grassland identification method based on sound wave reflection energy comprises a motion platform and a processor arranged in the motion platform, wherein an ultrasonic wave transmitting module and an ultrasonic wave receiving module are arranged at the bottom of the motion platform and are connected with the processor, a grassland identification algorithm is arranged in the processor, and the grassland identification method comprises the following steps of (1) transmitting ultrasonic waves by the processor at regular intervals, enabling the processor to carry out AD sampling on output signals of the ultrasonic wave receiving module at an interval of delta T after ultrasonic wave signals are transmitted, converting the output signals into digital sampling signals F (N), finishing the sampling process when the sampling time reaches delta T, wherein N = N, and (2) calculating the sum ∑ F = N of the sampling signals F (N) (3) if ∑ F<K, judging the lawn; otherwise, judging the lawn is not grassland.)

1. Grassland identification method based on sound wave reflection energy comprises a motion platform capable of moving autonomously, wherein a processor is arranged in the motion platform, and the grassland identification method is characterized in that: the bottom of the motion platform is provided with an ultrasonic transmitting module and an ultrasonic receiving module, the ultrasonic transmitting module and the ultrasonic receiving module are connected with the processor, a grassland identification algorithm is arranged in the processor to determine whether the position of the motion platform is grassland or not, and the grassland identification algorithm comprises the following steps:

(1) the processor transmits ultrasonic waves through the ultrasonic wave transmitting module at regular intervals, and converts the output signals of the ultrasonic wave receiving module into digital sampling signals f (n) after AD sampling at an interval of delta t after the ultrasonic wave signals are transmitted, wherein n =1,2, 3; when the sampling time reaches delta T, ending the sampling process, wherein N = N, delta T is the time interval from signal emission to signal sampling, delta T is a sampling time window, and N is the maximum sampling frequency;

(2) computing the sum ∑ F =of sampled signals F (n)；

(3) If sigma F is less than K, judging the lawn; otherwise, judging the lawn to be non-grassy, wherein K is an empirical threshold.

2. A method of acoustic reflection energy based grass identification as claimed in claim 1 wherein: the ultrasonic transmitting module is provided with an ultrasonic transmitting probe and a signal driving circuit, the ultrasonic receiving module is provided with an ultrasonic receiving probe and a signal amplifying circuit, and the ultrasonic transmitting probe and the ultrasonic receiving probe are arranged in a way that the axes are crossed and intersected with the ground.

Technical Field

The invention relates to a grassland identification method based on sound wave reflection energy, belonging to the technical field of mobile robots.

Background

The mowing robot needs to work on the lawn, otherwise, the mowing robot can cause danger to the mowing robot and flowers and trees around the lawn. For example, a sensor for detecting grass based on conductive characteristics is two electrodes installed at the bottom of the mowing robot, and when the mowing robot is on grass, blades of the grass have certain conductivity due to moisture and have a remarkable conductive characteristic relative to air. But this method fails to detect when the grass is sparse or too dry. In addition, the image-based grassland recognition method is a color-based discrimination method, and green is used as a recognition feature. But this method does not address the effect of changes in lighting conditions on imaging quality. At the same time, green sidewalks can also confuse the robot. Therefore, a perfect solution is needed for grassland recognition.

Disclosure of Invention

In order to solve the problems, the invention provides a grassland identification method based on sound wave reflection energy, which is used for identifying grasslands by using the obvious difference of the ultrasonic reflection characteristics of the grasslands and the common ground.

The technical scheme adopted by the invention for solving the technical problems is as follows:

the grassland identification method based on the sound wave reflection energy comprises a motion platform capable of moving autonomously, a processor is arranged in the motion platform, an ultrasonic transmitting module and an ultrasonic receiving module are installed at the bottom of the motion platform, the ultrasonic transmitting module and the ultrasonic receiving module are connected with the processor, a grassland identification algorithm is arranged in the processor, whether the position of the motion platform is grassland or not is confirmed, and the grassland identification algorithm comprises the following steps:

(1) the processor transmits ultrasonic waves through the ultrasonic wave transmitting module at regular intervals, and converts the output signals of the ultrasonic wave receiving module into digital sampling signals f (n) after AD sampling at an interval of delta t after the ultrasonic wave signals are transmitted, wherein n =1,2, 3; when the sampling time reaches delta T, ending the sampling process, wherein N = N, delta T is the time interval from signal emission to signal sampling, delta T is a sampling time window, and N is the maximum sampling frequency;

(2) computing the sum ∑ F =of sampled signals F (n)；

(3) If sigma F is less than K, judging the lawn; otherwise, judging the lawn to be non-grassy, wherein K is an empirical threshold.

The ultrasonic transmitting module is provided with an ultrasonic transmitting probe and a signal driving circuit, the ultrasonic receiving module is provided with an ultrasonic receiving probe and a signal amplifying circuit, and the ultrasonic transmitting probe and the ultrasonic receiving probe are arranged in a way that the axes are crossed and intersected with the ground.

The invention has the following beneficial effects: the reflected energy of the sound waves is analyzed, the grassland is identified according to the obvious difference of the grassland and the common ground on the reflection characteristic of the ultrasonic waves, non-contact detection is carried out, and the reliability is high.

Drawings

FIG. 1 is a functional block diagram of an embodiment of the present patent;

FIG. 2 is a schematic view showing the installation of an ultrasonic transmitting probe and an ultrasonic receiving probe;

fig. 3 is a schematic diagram of signal sampling.

Detailed Description

The invention is further described below with reference to the accompanying drawings:

referring to fig. 1-3, the grass identification method based on acoustic reflection energy comprises a moving platform capable of moving autonomously, wherein the moving platform can be provided with driving wheels and supporting wheels, and can realize execution, retreat and rotation at any angle. The processor 1 is arranged in the motion platform for centralized control. The bottom of the motion platform is provided with an ultrasonic transmitting module and an ultrasonic receiving module, the ultrasonic transmitting module is provided with an ultrasonic transmitting probe 3 and a signal driving circuit 2, the ultrasonic receiving module is provided with an ultrasonic receiving probe 5 and a signal amplifying circuit 4, and the processor 1 controls the signal driving circuit 2 to drive the ultrasonic transmitting probe 3 to transmit ultrasonic signals; the signal amplifying circuit 4 amplifies and filters the signal detected by the ultrasonic receiving probe 5, and transmits the signal to the processor 1. The ultrasonic transmitting probe 3 and the ultrasonic receiving probe 5 are arranged in a way that the axes are crossed and intersected with the ground, so that the best detection effect is achieved.

A grassland recognition algorithm is arranged in the processor 1 to determine whether the position of the motion platform is grassland or not, and the grassland recognition algorithm comprises the following steps:

(1) the processor 1 transmits ultrasonic waves through the ultrasonic wave transmitting module at regular intervals, and the processor 1 converts the output signal of the ultrasonic wave receiving module into a digital sampling signal f (n) after AD sampling at an interval of delta t after the ultrasonic wave signal is transmitted, wherein n =1,2, 3; when the sampling time reaches delta T, ending the sampling process, wherein N = N, delta T is the time interval from signal emission to signal sampling, delta T is a sampling time window, and N is the maximum sampling frequency;

the processor 1 performs signal sampling after an interval of Δ t time, so as to avoid direct interference of the ultrasonic transmitting probe 3 to the ultrasonic receiving probe 5. The Δ t time may be set to the shortest time from transmission to reception of the ultrasonic signal.

(2) Computing the sum ∑ F =of sampled signals F (n)；

The digital signal f (n) is a periodically attenuated signal, which represents the acoustic energy detected by the ultrasonic receiving probe 5, and under the condition of certain transmitted energy, the overall value can represent the reflection coefficient of the ground, and the reflection coefficient reflects the characteristics of the reflecting surface, i.e. the ground reflection coefficient is large, and the ground reflection coefficient is small, and based on the characteristics, the grassland and the common ground can be distinguished.

(3) If sigma F is less than K, judging the lawn; otherwise, judging the lawn to be non-grassy, wherein K is an empirical threshold.

The sigma F is used as a judgment basis, and is a numerical summation, and meanwhile, the method has the advantage of interference resistance. The K empirical threshold is used to distinguish ground from ground reflected energy.