Intelligent sensing application system of collaborative robot

Abstract

The utility model provides an intelligent sensing application system of a collaborative robot, which relates to the technical field of intelligent sensing of robots and comprises a control module, a visual detection module, a sound wave detection module, a positioning module and a speed detection module. The visual detection module can detect objects on the front side, the rear side, the left side and the right side of the robot through an image enhancement method, a machine learning algorithm and a convolutional neural network. Through the visual detection module and the speed detection module, an object on a moving path of the robot can be detected, a detection result is uploaded to the control module, the control module is assisted to control the robot to avoid the object in advance, and the robot can find and avoid obstacles in time; the collision probability between the robot and other equipment or objects is reduced, meanwhile, the sound wave detection module is matched, the speed of the objects can be detected, the moving track of the objects is simulated according to the moving direction and the moving speed of the objects, and risk pre-judgment is achieved.

Description

Technical Field

[0001] The utility model relates to a robot, in particular to a collaborative robot intelligent perception application system, belonging to the technical field of robot intelligent perception. Background Technique

[0002] A robot is an intelligent machine that can work semi-autonomously or fully autonomously. It has basic characteristics such as perception, decision-making, and execution, and can assist or even replace humans to complete dangerous, heavy, and complex tasks. Currently, most intelligent floor-sweeping robots are equipped with cameras as visual sensors to perceive the surrounding environment, use vision to identify the positions of people and robots, and control the robot to stop moving or avoid obstacles to ensure human safety. However, vision is sensitive to light. In poor lighting conditions, it is difficult to effectively perceive the environment. In addition, the visual sensor will be affected by the problem of object occlusion, resulting in visual blind spots and potential safety hazards. At the same time, in a relatively complex dynamic environment, the floor-sweeping robot cannot perform distributed acquisition and processing of relevant environmental and terrain road conditions factors, and cannot achieve risk perception and prediction, resulting in a reduction in the cleaning efficiency of the floor-sweeping robot. Content of the Utility Model

[0003] The utility model proposes a collaborative robot intelligent perception application system to solve the problem that risks cannot be perceived and predicted in a complex environment in the prior art.

[0004] The utility model is realized through the following technical solutions: A collaborative robot intelligent perception application system includes a control module, a visual detection module, a sound wave detection module, a positioning module, and a speed detection module;

[0005] The visual detection module can detect objects on the front, back, left, and right sides of the robot through image enhancement method, contour edge detection algorithm, filtering and noise reduction method, machine learning algorithm, and convolutional neural network;

[0006] The sound wave detection module sends short-pulse sound waves and records the echo signals generated after their interaction with the target object, and determines the distance and shape of the target object according to the time delay and intensity of the echo signals;

[0007] The speed detection module is used to detect the moving speed of the robot;

[0008] The visual detection module, the sound wave detection module, the positioning module, and the speed detection module are all signal-connected to the control module, and the control module is used to process the environmental information uploaded by the visual detection module, the distance information of the target object uploaded by the sound wave detection module, and the robot speed information uploaded by the speed detection module.

[0009] Further, the visual detection module includes a high-definition camera, a photoelectric sensor, and an infrared camera, and the acoustic wave detection module includes an ultrasonic sensor and an acoustic sensor array.

[0010] Further, it also includes a database and an autonomous navigation module. The database can store the floor plan of the working space and the historical movement route of the robot, and the autonomous navigation module can formulate the movement route of the robot according to the floor plan of the working space.

[0011] Further, the control module can construct a moving coordinate system centered on the robot, and the control module can mark the real-time coordinates of the objects detected by the visual detection module and the acoustic wave detection module in the moving coordinate system.

[0012] Further, the control module determines whether the object is on the movement route of the robot according to the real-time coordinates of the object, and judges the contact time according to the position data and speed data uploaded by the positioning module and the speed detection module, and performs deceleration and avoidance. After successful avoidance, the autonomous navigation module re-plans the travel route according to the current position.

[0013] Further, the positioning module is a GPS sensor, which is used to collect the real-time position information of the robot.

[0014] Further, the speed detection module also includes an inertial measurement unit, which is used to collect the acceleration and angular velocity information of the robot.

[0015] Further, the control module can adjust the detection ranges of the visual detection module and the acoustic wave detection module according to the moving speed of the robot.

[0016] Further, it also includes an emergency protection module and a communication module. The emergency protection module is used to control the robot to perform emergency protection when the collision between the robot and other devices or objects is inevitable, and the communication module is used for real-time communication with the operator and feedback on the task execution situation.

[0017] The present utility model provides a collaborative robot intelligent perception application system, and its beneficial effects are as follows:

[0018] 1. Through the mutual cooperation of the visual detection module and the speed detection module, the collaborative robot intelligent perception application system can detect the objects on the movement route of the robot, and upload the detection results to the control module to assist the control module to control the robot to avoid the objects in advance, enabling the robot to timely discover and avoid obstacles, reducing the collision probability between the robot and other devices or objects. At the same time, in cooperation with the acoustic wave detection module, it can detect the speed of the object, and simulate the movement trajectory of the object according to the moving direction and moving speed of the object to realize the prediction of risks.

[0019] 2. The intelligent perception application system of the collaborative robot is provided with a visual detection module and an acoustic wave detection module. The visual detection module is greatly affected by factors such as environmental light and occlusion, while the acoustic wave detection module is insensitive to environmental light and occlusion. Therefore, by combining the two detection modules, the stability and robustness of the system can be improved to adapt to a more complex detection environment. At the same time, the visual detection module usually takes a long time for image acquisition and processing, while the acoustic wave detection module can monitor the position and distance of an object in real time. By combining the two detection modules, faster real-time performance can be achieved while ensuring the accuracy and integrity of the detection results. Description of the Drawings

[0020] Figure 1 It is a diagram of the intelligent perception application system of the collaborative robot in the present utility model. Detailed Embodiment

[0021] Please refer to Figure 1 , an embodiment of the present utility model provides an intelligent perception application system of a collaborative robot, including a control module, a visual detection module, an acoustic wave detection module, a positioning module, and a speed detection module. The visual detection module can detect objects on the front, rear, left, and right sides of the robot through image enhancement method, contour edge detection algorithm, filtering and noise reduction method, machine learning algorithm, and convolutional neural network. The visual detection module can extract the morphological features of the object and convert them into multiple sets of coordinates according to the volume of the object. The acoustic wave detection module determines the distance and shape of the target object by sending short pulse acoustic waves and recording the echo signals generated after their interaction with the target object, based on the time delay and intensity of the echo signals. The intelligent perception application system of the collaborative robot is provided with a visual detection module and an acoustic wave detection module. The visual detection module is greatly affected by factors such as environmental light and occlusion, while the acoustic wave detection module is insensitive to environmental light and occlusion. Therefore, by combining the two detection modules, the stability and robustness of the system can be improved to adapt to a more complex detection environment. At the same time, the visual detection module usually takes a long time for image acquisition and processing, while the acoustic wave detection module can monitor the position and distance of an object in real time. By combining the two detection modules, faster real-time performance can be achieved while ensuring the accuracy and integrity of the detection results.

[0022] The visual detection module, the acoustic wave detection module, the positioning module, and the speed detection module are all signal-connected to the control module. The control module is used to process the environmental information uploaded by the visual detection module, the distance information of the target object uploaded by the acoustic wave detection module, and the robot speed information uploaded by the speed detection module. The control module can adjust the detection ranges of the visual detection module and the acoustic wave detection module according to the moving speed of the robot. The visual detection module includes a high-definition camera, a photoelectric sensor, and an infrared camera. The acoustic wave detection module includes a ultrasonic sensor and an acoustic sensor array.

[0023] It further includes a database and an autonomous navigation module. The database can store the floor plan of the working space and the historical moving route of the robot. The autonomous navigation module can formulate the moving route of the robot according to the floor plan of the working space. The control module can construct a moving coordinate centered on the robot, and the control module can mark the real-time coordinates of the objects detected by the visual detection module and the acoustic wave detection module in the moving coordinate system. The control module determines whether the object is on the moving route of the robot according to the real-time coordinates of the object, and judges the contact time according to the position data and speed data uploaded by the positioning module and the speed detection module, and performs deceleration and avoidance. After the avoidance is successful, the autonomous navigation module re-plans the travel path according to the current position. Through the mutual cooperation of the visual detection module and the speed detection module, this collaborative robot intelligent perception application system can detect the objects on the moving path of the robot, and upload the detection results to the control module to assist the control module to control the robot to avoid the objects in advance, enabling the robot to timely detect and avoid obstacles, reducing the collision probability between the robot and other devices or objects. At the same time, in cooperation with the acoustic wave detection module, it can detect the speed of the object, and simulate the moving trajectory of the object according to the moving direction and moving speed of the object to achieve the prediction of risks.

[0024] The positioning module is a GPS sensor, which is used to collect the real-time position information of the robot. The speed detection module is used to detect the moving speed of the robot. The speed detection module further includes an inertial measurement unit, which is used to collect the acceleration and angular velocity information of the robot.

[0025] It further includes an emergency protection module and a communication module. The emergency protection module is used to control the robot to perform emergency protection when the collision between the robot and other devices or objects is inevitable. The communication module is used for real-time communication with the operator and feedback on the task execution situation.

[0026] On this basis, it also includes a speech recognition module, enabling the robot to receive, understand, and execute tasks in real time through voice commands; by combining the speech recognition module with natural language processing technology, the robot can more accurately understand complex instructions and communicate more naturally with the operator.

[0027] When the control module controls the autonomous navigation module to formulate a movement route according to the floor plan of the working space, a real-time path planning algorithm is introduced, combined with the floor plan data, enabling the robot to select the optimal path to the designated location; at the same time, a reinforcement learning algorithm is adopted, enabling the robot to dynamically adjust the path according to real-time environmental changes and improve adaptability.

[0028] When judging the contact time based on the position data and speed data uploaded by the positioning module and the speed detection module and performing deceleration and avoidance, a real-time motion planning algorithm is combined, along with sensor data and a machine learning model, enabling the robot to adjust the motion strategy in a timely manner according to the real-time position and speed data to avoid obstacles and ensure safety.

[0029] Finally, using the reinforcement learning algorithm and model prediction technology, the robot can learn from the avoidance experience, improve the avoidance efficiency, and avoid the recurrence of similar obstacles.

[0030] Working principle: First, place the device in the designated working space and store the floor plan of the working space in the database in advance. Subsequently, the staff issues a cleaning instruction to the robot. The control module controls the autonomous navigation module to formulate a movement route according to the floor plan of the working space. Then, the control module constructs a moving coordinate centered on the robot. Next, the control module controls the visual detection module and the acoustic wave detection module to scan and detect the surrounding environment of the robot. Then, the control module determines whether the object is on the movement route of the robot based on the environmental information uploaded by the visual detection module and the target object information uploaded by the acoustic wave detection module, and judges the contact time based on the position data and speed data uploaded by the positioning module and the speed detection module, and performs deceleration and avoidance. After successful avoidance, the autonomous navigation module re-plans the travel route according to the current position.

[0031] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A collaborative robot intelligent perception application system, characterized by: It includes a control module, a visual detection module, an acoustic wave detection module, a positioning module and a speed detection module; The visual detection module can detect objects in front of and behind the robot and on the left and right sides through image enhancement method, contour edge detection algorithm, filtering noise reduction method, machine learning algorithm and convolutional neural network; The acoustic wave detection module sends short pulse acoustic waves and records the echo signals generated after the acoustic waves interact with the target object, and determines the distance and shape of the target object according to the time delay and intensity of the echo signals; The speed detection module is used to detect the moving speed of the robot; The visual detection module, the acoustic wave detection module, the positioning module and the speed detection module are all connected to the control module signal, and the control module is used to process the environmental information uploaded by the visual detection module, the distance information of the target object uploaded by the acoustic wave detection module and the robot speed information uploaded by the speed detection module.

2. The collaborative robot intelligent perception application system according to claim 1, characterized in that: It also includes a database and an autonomous navigation module. The database can store the plan view of the workspace and the historical movement route of the robot. The autonomous navigation module can formulate the movement route of the robot according to the plan view of the workspace.

3. The collaborative robot intelligent perception application system according to claim 2, characterized in that: The control module can construct a mobile coordinate system centered on the robot, and the control module can mark the real-time coordinates of the object detected by the visual detection module and the acoustic wave detection module in the mobile coordinate system.

4. The collaborative robot intelligent perception application system according to claim 3, characterized in that: The control module determines whether the object is on the robot's moving route based on the object's real-time coordinates, and determines the contact time based on the position data and speed data uploaded by the positioning module and the speed detection module, and decelerates to avoid the object. After the avoidance is successful, the autonomous navigation module replans the travel path based on the current position.

5. The collaborative robot intelligent perception application system according to claim 1, characterized in that: The positioning module is a GPS sensor, which is used to collect the real-time position information of the robot.

6. The collaborative robot intelligent perception application system according to claim 1, characterized in that: The speed detection module also includes an inertial measurement unit for collecting acceleration and angular velocity information of the robot.

7. The collaborative robot intelligent perception application system according to claim 1, characterized in that: The control module can adjust the detection ranges of the visual detection module and the sound wave detection module according to the moving speed of the robot.

Images