Robot safety monitoring system

Abstract

The invention discloses a robot safety monitoring system which comprises a sensor module, a sensing module, a positioning module, a hardware monitoring module, a software monitoring module, a planning control module, an early warning module, a record feedback module and a robot control system. Identifying and analyzing objects and obstacles in the working environment; and the planning control module is used for generating a driving path and performing real-time adjustment according to the sensing and positioning information. According to the robot safety monitoring system provided by the invention, the laser radar, the camera and other multi-element sensors are fused, a high-precision environment map is constructed, and autonomous navigation of the robot can be realized in combination with the positioning module; the early warning module performs graded early warning according to abnormal conditions to ensure operation safety; the hardware monitoring module and the software monitoring module work cooperatively to guarantee stable operation of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of robots, and in particular to a robot safety monitoring system. Background Art

[0002] With the rapid development of robotics technology, robots are increasingly used in various fields. Existing robot safety monitoring systems often have some problems when dealing with complex and changing environments. First, the existing system cannot handle environmental changes in real time, resulting in the robot being unable to avoid new obstacles in time, which not only reduces driving efficiency but also increases safety hazards. Secondly, traditional systems are too slow and time-consuming when searching for paths, and the generated paths are often difficult to ensure feasibility and optimality, which greatly limits the application scope and effectiveness of robots.

[0003] These problems not only affect the robot's operating efficiency, but also increase the risk of operating in a dynamic environment. Therefore, a new solution is urgently needed to improve the robot's autonomous perception ability and the intelligent level of path planning to ensure the robot's safe and efficient operation in a changing environment. Summary of the invention

[0004] In view of the shortcomings of the current existing technology, the present invention provides a robot safety monitoring system, which realizes real-time monitoring and accurate analysis of the robot's surrounding environment by integrating sensor modules and perception, positioning, planning and control technologies, and can quickly respond to environmental changes and generate feasible driving paths.

[0005] To achieve the above object, the embodiments of the present invention adopt the following technical solutions: A robot safety monitoring system, comprising a sensor module, a perception module, a positioning module, a hardware monitoring module, a software monitoring module, a planning control module, an early warning module, a recording feedback module and a robot control system; The output end of the sensor module is connected to the hardware monitoring module, the perception module and the positioning module, and the output end of the software monitoring module is connected to the early warning module; the output end of the hardware monitoring module is connected to the software monitoring module and the early warning module; the perception module and the positioning module are connected in parallel and then connected to the software monitoring module and the planning control module; the output end of the planning control module is connected to the software monitoring module and the robot control system; the output end of the robot control system is connected to the hardware monitoring module and the recording feedback module; The perception module is used to process sensor data, identify and analyze objects and obstacles in the working environment; the planning and control module is used to generate a driving path and adjust it in real time based on the perception and positioning information.

[0006] In one embodiment, the perception module identifies and analyzes objects and obstacles in the working environment by: The perception module removes sensor data noise through a low-pass filter, converts the processed sensor data from polar coordinates to Cartesian coordinates, and extracts key image features through edge detection; The extracted image features are input into the pre-trained YOLO target detection model for classification and recognition, and the recognition results and target bounding boxes are output; Combine sensor data, use triangulation to calculate the object position, fuse multiple sets of sensor data to obtain better environmental understanding, and feed the recognition results back to the planning and control module.

[0007] In one embodiment, the planning control unit generates a driving path by the following steps: Build an environment map based on sensor data, positioning data and perception module recognition results, use a grid map to represent the environment, and assign values ​​to the grids based on the perception module recognition results; Initialize a set of population individuals, pheromone concentrations of each grid, heuristic values, and pheromone volatility, and determine the robot's next moving node through simulated movement and selection probability calculation; The robot traverses the environment to the target point, records the path, calculates the quality and feasibility of the path, and updates the pheromone; The grid selection and path construction are repeated many times, and the path with the highest pheromone concentration is selected as the optimal driving path, and the optimal path is converted into robot control instructions through the PID controller.

[0008] In one embodiment, assigning a value to the grid according to the recognition result of the perception module specifically includes: assigning a value of 1 or 0 to the grid, if the grid value is 1, it means that the grid is passable, if the grid value is 0, it means that the grid is not passable.

[0009] In one embodiment, the hardware monitoring module includes a power monitoring unit, an environment monitoring unit, and a sensor monitoring unit; the power monitoring unit is used to monitor the stability of the robot's power supply in real time, the environment monitoring unit is used to monitor the temperature and air pressure of the working environment, and the sensor monitoring unit is used to detect the working status of the sensor in real time.

[0010] In one embodiment, the software monitoring module includes a heartbeat detection unit, a perception monitoring unit, a positioning monitoring unit, and a planning monitoring unit; the heartbeat detection module is used to periodically send heartbeat messages to detect the status of each module, the perception monitoring unit is used to monitor the output of the perception module, and the positioning monitoring unit is used to monitor the calculation results of the positioning module in real time to identify the accuracy of the robot's positioning information.

[0011] In one embodiment, the sensor module includes a laser radar, a camera, an ultrasonic sensor, an IMU, a tactile sensor, and an infrared sensor.

[0012] In one embodiment, the early warning module sends log messages, lamp prompts and voice prompts in different levels according to different types of abnormal situations.

[0013] The beneficial effects of the present invention are that it provides a robot safety monitoring system that can process environmental changes in real time, quickly adjust the path, ensure that the robot can avoid new obstacles, and improve the robot's driving efficiency and safety; it has good distributed characteristics, can speed up the path finding speed, and ensure that the generated path is feasible; by integrating multiple sensors and positioning technologies, it can achieve high-precision environmental perception and positioning functions; the early warning module can automatically adjust the prompt priority according to different levels of abnormal situations, ensuring that the operator can obtain important information in time; the recording feedback module can record and analyze data in real time, and provide support for system optimization and improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 This is a schematic diagram of the connection of various modules of the robot safety monitoring system of the present invention; Figure 2 It is a structural diagram of the hardware monitoring module of the present invention; Figure 3 It is a structural schematic diagram of the software monitoring module described in the present invention. DETAILED DESCRIPTION

[0016] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0017] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] like Figure 1 , Figure 2 and Figure 3 As shown, this embodiment provides a robot safety monitoring system, including a sensor module, a perception module, a positioning module, a hardware monitoring module, a software monitoring module, a planning control module, an early warning module, a recording feedback module and a robot control system.

[0020] The connection mode of each module is as follows: the output end of the sensor module is connected to the hardware monitoring module, the perception module and the positioning module, and the output end of the software monitoring module is connected to the early warning module; the output end of the hardware monitoring module is connected to the software monitoring module and the early warning module; the perception module and the positioning module are connected in parallel and then connected to the software monitoring module and the planning control module; the output end of the planning control module is connected to the software monitoring module and the robot control system; the output end of the robot control system is connected to the hardware monitoring module and the recording feedback module. In this embodiment, each module is connected through a CAN bus. This connection mode can realize fast communication and data sharing between modules, and improve the overall performance and reliability of the system.

[0021] The hardware monitoring module includes a power monitoring unit, an environment monitoring unit, and a sensor monitoring unit. The power monitoring unit is used to monitor the stability of the robot's power supply in real time to ensure that the robot can continue to operate stably. The environment monitoring unit is used to monitor the temperature and air pressure parameters of the working environment. When the environmental parameters exceed the set range, it can automatically send a warning signal to the robot control system. The sensor monitoring unit is used to detect the working status of various sensors in real time to ensure the accuracy and reliability of sensor data.

[0022] The sensor module is used to collect real-time data on the robot's surrounding environment. It includes lidar, cameras, ultrasonic sensors, IMU (inertial measurement unit), tactile sensors and infrared sensors. The above sensors can fully perceive the robot's surrounding environment and provide data support for subsequent perception and planning.

[0023] The software monitoring module includes a heartbeat detection unit, a perception monitoring unit, a positioning monitoring unit, and a planning monitoring unit. The heartbeat detection module is used to periodically send heartbeat messages to detect whether each module is online and working properly, and trigger an alarm when the heartbeat is abnormal. The perception monitoring unit is used to monitor the output of the perception module to ensure the accuracy of the perception results. The positioning monitoring unit is used to monitor the calculation results of the positioning module in real time and identify the accuracy of the robot's positioning information. The planning monitoring unit is used to monitor the rationality of path planning and control decisions to ensure that the robot can travel along the optimal path.

[0024] The perception module is used to process sensor data and identify and analyze objects and obstacles in the working environment. The perception module identifies and analyzes objects and obstacles in the working environment through the following steps: S1.1: The perception module removes noise from each set of data collected by each sensor through a low-pass filter, converts the processed sensor data from polar coordinates to Cartesian coordinates, and extracts key image features from the image data collected by the camera through edge detection; S1.2: Pre-train a group of YOLO target detection models, input the extracted image data features of each group into the pre-trained YOLO target detection model, the YOLO target detection model classifies and recognizes the extracted features, and outputs the recognition results and the corresponding target bounding box; S1.3: Combine the identified object information with the sensor data, use triangulation to calculate the position of the object information in space, fuse multiple sets of sensor data to obtain a better understanding of the environment, and feed back the detected object and obstacle position information to the planning and control module.

[0025] The planning control module is used to generate a driving path and make real-time adjustments based on the perception and positioning information. The planning control unit generates the driving path through the following steps: S2.1: Based on the sensor data, positioning data and the recognition results of the perception module, an environmental map of the robot's environment is constructed. The environment is represented by a grid map, and each grid is assigned a value according to the recognition results of the perception module. Specifically, the grid is assigned a value of 1 or 0. If the grid value is 1, it means that the grid is passable. If the grid value is 0, it means that the grid is impassable. S2.2: Initialize a set of population individuals, pheromone concentrations of each grid, heuristic values, and pheromone volatility rates, take the current position of the robot as the initial position, place each group of individuals at the initial position, perform simulated movement, calculate the selection probability of the subsequent movable grid according to the pheromone concentration and heuristic information, and randomly select a grid as the next moving node of the robot based on the calculated selection probability; S2.3: The robot is triggered from the starting point, traverses the environment to the target point, stops selecting, records the complete path, and calculates the path quality and feasibility. Then, the pheromone on the path is updated according to the path quality found by each individual; S2.4: Repeat the grid selection and path construction multiple times until the maximum number of iterations is reached, traverse all constructed paths, select the path with the highest pheromone concentration as the optimal driving path for the robot, and convert the optimal path into robot control instructions through the PID controller to guide the movement of the robot. During the robot's driving process, it continuously monitors environmental changes and adjusts the path in real time.

[0026] The positioning module is used by the robot to obtain its own position in real time, and to perform navigation and path planning. By integrating multiple positioning technologies, such as GPS and inertial navigation, high-precision positioning functions can be achieved.

[0027] The early warning module sends log messages, light tube prompts and voice prompts according to different types of abnormal situations. When an abnormal situation is detected, the priority of log messages, light tube prompts and voice prompts can be automatically adjusted to ensure that operators can obtain important information in a timely manner and take corresponding countermeasures. The above abnormal situations include: prompts, such as heavy load, turning, insufficient power, full log; warnings, such as overheating, excessive load, current and voltage overload, etc.; faults, such as sensor damage, battery abnormality, software module abnormality, heartbeat message loss, etc.

[0028] The robot control system is used to modify the robot's path, control the motor to stop, or control the power to shut down, etc., according to the type of abnormal situation detected. By integrating multiple control algorithms and strategies, the robot's autonomous control and safety protection can be achieved.

[0029] The recording and feedback module is used to record all monitoring data and warning information, and feed it back to the robot control system. By real-time recording and analyzing data, potential problems can be discovered in time and optimization and improvement can be carried out.

[0030] In practical applications, the robot described in this embodiment collects surrounding environment data in real time through the sensor module, processes and analyzes it through the perception module, and the planning control module generates a safe form path based on the perception and positioning information, and adjusts it in real time to cope with environmental changes. At the same time, the software monitoring module monitors and detects each module in real time to ensure the normal operation of the system. When an abnormal situation is detected, the early warning module will issue a corresponding prompt message, and the robot control system will take corresponding countermeasures according to the type of abnormal situation. The recording feedback module records all monitoring data and early warning information, and feeds it back to the robot control system for analysis and processing.

[0031] Through the above technical solutions, the robot safety monitoring system of this embodiment can handle environmental changes in real time, quickly adjust the path, and ensure the robot's driving efficiency and safety. At the same time, it has good distributed characteristics and path finding speed, can generate feasible driving paths, and enable the robot to operate stably in different environments.

[0032] The above embodiments are preferred implementation schemes of the present invention. In addition, the present invention can also be implemented in other ways. Any obvious replacement without departing from the concept of the present technical solution is within the scope of the patent of the present invention.

[0033] In order to make it easier for ordinary technicians in the field to understand the improvements of the present invention over the prior art, some drawings and descriptions of the present invention have been simplified, and for the sake of clarity, some other elements are omitted in this application document. Ordinary technicians in the field should realize that these omitted elements may also constitute the content of the present invention.

Claims

1. A robot safety monitoring system, characterized in that: It includes sensor module, perception module, positioning module, hardware monitoring module, software monitoring module, planning control module, early warning module, recording feedback module and robot control system; The output end of the sensor module is connected to the hardware monitoring module, the perception module and the positioning module, and the output end of the software monitoring module is connected to the early warning module; the output end of the hardware monitoring module is connected to the software monitoring module and the early warning module; the perception module and the positioning module are connected in parallel and then connected to the software monitoring module and the planning control module; the output end of the planning control module is connected to the software monitoring module and the robot control system; the output end of the robot control system is connected to the hardware monitoring module and the recording feedback module; The perception module is used to process sensor data, identify and analyze objects and obstacles in the working environment; the planning and control module is used to generate a driving path and adjust it in real time based on the perception and positioning information.

2. The robot safety monitoring system according to claim 1, characterized in that: The perception module identifies and analyzes objects and obstacles in the working environment through the following steps: The perception module removes sensor data noise through a low-pass filter, converts the processed sensor data from polar coordinates to Cartesian coordinates, and extracts key image features through edge detection; The extracted image features are input into the pre-trained YOLO target detection model for classification and recognition, and the recognition results and target bounding boxes are output; Combine sensor data, use triangulation to calculate the object position, fuse multiple sets of sensor data to obtain better environmental understanding, and feed the recognition results back to the planning and control module.

3. The robot safety monitoring system according to claim 1, characterized in that: The planning control unit generates a driving path by the following steps: Build an environment map based on sensor data, positioning data and perception module recognition results, use a grid map to represent the environment, and assign values ​​to the grids based on the perception module recognition results; Initialize a set of population individuals, pheromone concentrations of each grid, heuristic values, and pheromone volatility, and determine the robot's next moving node through simulated movement and selection probability calculation; The robot traverses the environment to the target point, records the path, calculates the quality and feasibility of the path, and updates the pheromone; The grid selection and path construction are repeated many times, and the path with the highest pheromone concentration is selected as the optimal driving path, and the optimal path is converted into robot control instructions through the PID controller.

4. The robot safety monitoring system according to claim 3, characterized in that: The assigning of values ​​to the grid according to the recognition result of the perception module specifically includes: assigning a value of 1 or 0 to the grid, if the grid value is 1, it indicates that the grid is passable, and if the grid value is 0, it indicates that the grid is impassable.

5. The robot safety monitoring system according to claim 1, characterized in that: The hardware monitoring module includes a power monitoring unit, an environment monitoring unit, and a sensor monitoring unit; the power monitoring unit is used to monitor the stability of the robot's power supply in real time, the environment monitoring unit is used to monitor the temperature and air pressure of the working environment, and the sensor monitoring unit is used to monitor the working status of the sensor in real time.

6. The robot safety monitoring system according to claim 1, characterized in that: The software monitoring module includes a heartbeat detection unit, a perception monitoring unit, a positioning monitoring unit, and a planning monitoring unit; the heartbeat detection module is used to periodically send heartbeat messages to detect the status of each module, the perception monitoring unit is used to monitor the output of the perception module, and the positioning monitoring unit is used to monitor the calculation results of the positioning module in real time to identify the accuracy of the robot's positioning information.

7. The robot safety monitoring system according to claim 1, characterized in that: The sensor module includes a laser radar, a camera, an ultrasonic sensor, an IMU, a tactile sensor and an infrared sensor.

8. The robot safety monitoring system according to claim 1, characterized in that: The early warning module sends log messages, lamp prompts and voice prompts in different levels according to different types of abnormal situations.

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