34 results about "PatrolBot" patented technology

This invention provides an emergency response system, method, and medium for urban storage tanks based on a large-scale Internet of Things (IoT) model, relating to the field of urban storage tank emergency response. The method includes: acquiring the operating status of the storage tank at a first preset time; determining a state change value of the storage tank based on the operating status; in response to the state change value satisfying a first preset condition: acquiring storage tank monitoring data, and determining emergency control parameters based on the monitoring data, the emergency control parameters including the water mist spraying speed of a cooling device; and controlling the cooling device to spray water mist onto the outer wall of the storage tank based on the emergency control parameters. This method can promptly trigger an emergency mechanism in the early stages of an anomaly; and by using patrol robots to replace manual inspections of the area where the storage tank is located, while simultaneously collecting data in real time, it can improve inspection efficiency, the accuracy of safety warnings, and reduce the safety risks of the storage tank.

The invention discloses a self-adaptive navigation system and method for an outdoor patrol robot, and belongs to the technical field of robot navigation. The problems that an existing patrol robot is poor in path adaptability, complex scene navigation stability is insufficient, and the intelligent degree is low are solved. The core of the technical scheme is that an original path is optimized through an angle constraint iterative smoothing algorithm, an included angle between adjacent line segments is calculated and corrected, a path point is adjusted in combination with a maximum allowable rotation angle of a robot chassis, and path smoothness and kinematics constraint matching are ensured through double iteration termination conditions; segmenting according to lane attribute consistency, and dividing path segments based on a preset attribute vector and a trigger condition; and finally, the robot adaptively adjusts a navigation strategy according to the attributes of each section. The method improves the path tracking precision and the driving stability, enhances the adaptability of the robot to different outdoor scenes, does not need complex manual calibration, reduces the operation and maintenance cost, and can be widely applied to unmanned patrol of multiple scenes such as parks and factories.

1.The name of the design product is: four-legged security patrol robot. 2.The use of the design product is: for indoor and outdoor all-terrain, all-scene, all-weather intelligent mobile monitoring and detection patrol, real-time information timely uploading to the background, finding abnormalities and timely notifying relevant personnel. 3.The design points of the design product are: the combination of shape and pattern. 4.The picture or photo that best indicates the design points is: perspective view.

The invention is suitable for the technical field of artificial intelligence, and provides a patrol robot task interruption processing method, which comprises the following steps: after a task interruption signal of a first patrol robot is received, first task information of a task originally executed by the first patrol robot is acquired, and the task interruption signal comprises interruption time and an interruption place; determining a first cost value of the originally executed task based on the first task information; if the first cost value is greater than a preset first cost value threshold value, scheduling a second patrol robot to execute an originally executed task based on the interruption time and the interruption place; and if the first cost value is smaller than a preset first cost value threshold value, the first patrol robot is scheduled to continue to execute the originally executed task. According to the method, interruption with low cost value is continuously executed by the original robot; and the interruption with high cost value is replaced by other robots, so that the empty driving range and the electric energy consumption of the robot are reduced, the endurance operation time of the robot is prolonged, and the task interruption handling efficiency is improved.

The invention discloses a hierarchical self-adaptive safety reinforcement learning system and method applied to a patrol robot, and the method comprises the steps: introducing a hierarchical safety factor strategy pool and a self-adaptive safety element strategy, and optimizing a potential risk assessment function through an SFGA; according to the method, the safety violation times (such as entering a forbidden area and colliding with a dynamic / static object too close to the forbidden area) can be comprehensively and remarkably reduced, and the average minimum safety distance is increased, so that dangerous behaviors are effectively avoided.

1. The name of the design product: patrol robot. 2. The use of the design product: patrol robot for mobile or fixed security, patrol monitoring in different scenes. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses an autonomous patrol robot and an intelligent power grid peccancy detection method, the autonomous patrol robot comprises a four-wheel differential chassis and a control center, the control center remotely controls the four-wheel differential chassis, and the four-wheel differential chassis comprises an inertial navigation module, a dual-light camera, a self-tracking module, a four-way electronic speed controller module and an embedded driving module; the control center comprises a voice talkback module; the method comprises the steps that the dual-light camera shoots a field image and inputs the field image into the target detection model network, the target detection model network detects the field image and generates corresponding field image data, and the self-tracking module identifies violation information in the field image data according to a sample database and detects a corresponding violation object at the same time. The control center receives violation information and sends a corresponding tracking instruction to the embedded driving module, the control center stores the violation information and a corresponding violation object, and the embedded driving module drives the autonomous patrol robot to move to the violation object according to the tracking instruction.

1. The name of the design product: water patrol robot. 2. The use of the design product: for marine investigation, water quality monitoring, hydrological survey, unmanned scientific research, water patrol and other water activities. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective drawing.

1. Name of the product in this design: Security Patrol Robot. 2. Purpose of this design: Robot for security patrol. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

Provided are an early warning and emergency device for a sudden stress change in surrounding rock and a method of use, which relates to the technical field of underground mining. The device includes a front shell, a rotating body, a rear shell, a driving device, a stress monitoring unit, an acoustic and optical early warning unit, a high-pressure jet mechanism, and a data analysis controller. By using the device of the present disclosure, a cloud map of sudden stress changes in surrounding rock can be formed in real time, timely monitoring can be carried out in a case where the stress in the surrounding rock undergoes a high-intensity sudden change, the self-positioning temporary patrol robot is mobilized to perform temporary support for the sudden stress change point of the surrounding rock and timely transmit a sudden stress change early warning signal to remind nearby workers to evacuate in time.

The application discloses a kind of based on patrol robot's fall behavior detection method, comprising: control patrol robot moves in preset place, and the image signal of the preset place is collected;Image information is detected for fall behavior, and the human body information of suspected fall state is obtained;The key point detection is carried out to the human body information of suspected fall state, and the human body key point information and its confidence are obtained;According to the filtering logic of preestablished, the human body key point information and its confidence are screened, and fall behavior person is obtained.The application effectively solves the problems of missing detection and false detection, complex deployment and high detection cost in the prior art when detecting fall behavior.

This invention relates to the field of DQN algorithm technology, and particularly to an autonomous navigation method for an indoor patrol robot based on an improved DQN algorithm. The method includes: S1, the patrol robot perceives its surrounding environment and combines this with its own position information and the target points it intends to reach to form a state space. Several target points are sequentially set in the state space and used as inputs to the DQN algorithm; S2, the objective function of the DQN algorithm is improved so that the target points continuously change from starting points until the last target point; S3, the convergence speed of the DQN algorithm is improved by modifying the reward / penalty function r. This invention improves the DQN algorithm to avoid the problem of the algorithm getting stuck in an infinite loop; it segments the robot's path, greatly reducing the number of iterations of the DQN algorithm; and it accelerates the convergence speed of the DQN algorithm by improving the reward / penalty function, thereby completing the task of autonomous navigation for the indoor patrol robot.

The invention is suitable for the technical field of artificial intelligence, and provides a mobile booth tracking method, which comprises the following steps: when a fixed camera in a current area detects a mobile booth to be tracked, determining event persistence and a moving direction of the mobile booth to be tracked; according to the event persistence and the moving direction, determining a next area to which the to-be-tracked flowing stall goes; if the untrackable distance between the next area and the current area is greater than the preset distance, searching a patrol robot in a predetermined area; wherein the preset distance is dynamically set according to the event occurrence probability between the current area and the next area; and when the event discovery probability of the patrol robot is smaller than a preset event discovery probability, scheduling the patrol robot to execute a tracking task for the to-be-tracked event between the current area and the next area. According to the invention, through cooperation of the fixed camera and the patrol robot, cross-region seamless continuous tracking of the mobile stalls is realized, and the resource utilization efficiency is improved.

1. The name of the design product: security inspection robot. 2. The use of the design product: the appearance design for security patrol robot, realizing autonomous inspection, real-time monitoring and abnormal warning function, assisting or replacing manual security operation. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: design 1 perspective view 1. 5. Design 1 is designated as the basic design.

The patrol robot comprises a main body, a plurality of ultrasonic sensors, a panorama camera, a thermal image camera, a plurality of gas sensors and a UWB (Ultra Wideband) positioning following module, the main body comprises an upper assembly component and a moving component used for driving the upper assembly component to walk along the surface of a medium, and the moving component is used for driving the upper assembly component to move along the surface of the medium. The upper assembly component comprises an installation platform, an electric cabinet and an upper assembly shell, the ultrasonic sensors are fixed to the installation platform through front, rear, left and right installation supports respectively, the panorama camera is arranged on the upper side of the front portion of the upper assembly shell, the thermal image camera is arranged at the front end of the upper assembly shell, and a plurality of sensor fixing covers are arranged on the electric cabinet. The gas sensor is detachably mounted in the sensor fixing cover, and the UWB positioning following module is mounted in the upper mounting component. The patrol robot can replace human beings to carry out patrol operation, so that the personal safety of the human beings, especially police officers is guaranteed, and the patrol robot is diversified in function, reasonable in layout and suitable for autonomous patrol in various complex environments.

1. Name of the product in this design: Inspection and Patrol Robot (Gun Shape). 2. Purpose of this design: For indoor and outdoor all-weather intelligent mobile monitoring, hazard monitoring, environmental monitoring, visual inspection, and timely notification of relevant personnel upon detection of abnormalities. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the key design points: Design 1 3D diagram 1. 5. Design 1 is designated as the basic design.

The invention relates to the technical field of campus security and protection management, in particular to a smart campus intelligent security and protection early warning system, which comprises a data acquisition module used for acquiring campus security and protection data through a multi-dimensional security and protection device and a patrol robot; the vulnerability thermodynamic diagram construction module is used for constructing a risk simulation model to calculate the security vulnerability coefficient of each geographic grid unit of the campus, dividing risk levels and generating a vulnerability thermodynamic diagram; the early warning module is used for carrying out multi-dimensional analysis, identifying a security anomaly type and triggering corresponding early warning; the patrol scheduling module is used for dynamically planning patrol routes of the patrol robots, and when early warning is triggered, the patrol robot closest to an early warning area is scheduled to go to the site for checking; and the role collaboration module is used for pushing differentiated tasks to different security roles based on the risk level distribution and the early warning type of the vulnerability thermodynamic diagram. Therefore, the problems of single data dimension, risk perception lagging, resource scheduling stiffness, low efficiency of multi-role collaboration and the like are solved.

The invention provides a base station for a courtyard robot and a cleaning system. The base station for the courtyard robot comprises a power supply assembly and a base capable of being electrically connected with the power supply assembly. The base comprises a charging part, and the charging part is in butt joint with different types of courtyard robots so as to charge the courtyard robots. The courtyard robot at least comprises a mowing robot, a swimming pool cleaning robot, a snow removing robot, an intelligent irrigation robot, a fallen leaf cleaning robot or a courtyard security patrol robot. The charging part can be in butt joint with different types of courtyard robots to charge the different types of courtyard robots, so that the base station for the courtyard robot has high universality and adaptability and can be at least used as a charging platform for the different types of courtyard robots.

The invention relates to the technical field of robots, and particularly discloses a 5G-based security patrol robot which comprises a robot body shell, a camera is fixedly connected to the top of the robot body shell, jacking assemblies penetrate through and are slidably connected to the top of the robot body shell, and the two jacking assemblies are symmetrically distributed at the top of the robot body shell; universal driving wheels are uniformly and fixedly connected to the bottom of the machine body shell, mounting frames are fixedly connected to the two sides of the inner wall of the machine body shell, a double-shaft driving motor is fixedly connected to the ends, away from the machine body shell, of the mounting frames, and first rotating shafts are fixedly connected to driving shafts at the two ends of the double-shaft driving motor; the security patrol robot based on 5G is provided with a rain shielding device, so that the robot can be prevented from being damaged by rainy and snowy weather, and the security patrol robot based on 5G is provided with a fire extinguishing device, so that an abnormal fire source can be extinguished in time when encountering the abnormal fire source, and fire disasters are avoided.

The application discloses a patrol robot voice interaction system with environment sensing capability, and has the characteristics that it comprises an environment voiceprint modeling module, an acoustic interference identification module, an instruction double confirmation module, a semantic coupling verification module, a confidence dynamic adjustment module and an instruction behavior consistency filtering module; the environment voiceprint modeling module constructs an environment voiceprint real-time extraction module with a frequency domain redundancy analysis mechanism, continuously collects environment acoustic signals on a patrol path, and constructs a frequency band mapping vector based on the collected acoustic signals; the application has the advantages that it can accurately identify the voice mis-triggering risk in a high-noise environment, and improve the identification robustness through the semantic verification and double confirmation mechanism; meanwhile, the confidence dynamic adjustment and behavior consistency filtering are combined to realize the context rationality judgment of the control instruction, and ensure the safe and reliable execution of the instruction.

The invention discloses a patrol robot control method and system based on path optimization, relates to the technical field of intelligent security and protection, and solves the problems that in the prior art, an optimization decision is often started based on a specific threshold value, the decision threshold value cannot be adaptively adjusted according to the environment and the robot state, and the safety is poor. And the working efficiency and the working precision of the patrol robot are relatively low. The monitoring confusion degree is generated based on the monitoring data; when the monitoring confusion degree exceeds a monitoring threshold value, adjusting a patrol path and equipment parameters based on the patrol area data and the patrol data; when the equipment battery value is smaller than the battery threshold value, collaborative planning data of multi-robot collaborative patrol is generated based on the patrol data, and monitoring threshold values in different areas are adjusted in real time through the environment and robot states, so that the robots in the different areas are more efficient and accurate during path optimization; therefore, the efficiency and the precision of the patrol robot control method are improved.

To provide a lifting structure for an imaging assembly of a patrol robot, which has a simple structure, a rational design, and is advantageous in terms of easy attachment / detachment and maintenance. [Solution] The imaging assembly lifting structure of the patrol robot of the present invention includes an electric push rod C1 vertically fixed to the upper surface of a base plate and a plurality of telescopic slide rails, the telescopic free end of the electric push rod being connected to the free ends of the plurality of telescopic slide rails, each slide rail being fixedly connected to a seat plate C3 and at least one imaging assembly fixed to the seat plate. The present invention can sequentially lift and lower each section of the plurality of telescopic slide rails by operating the electric push rod, and further, link the lifting and lowering of the seat plate connected to the slide rail of each section and the imaging assembly on the seat plate, so that the imaging assembly can perform video scanning or image capture of poultry in different floors of poultry barns.

The application discloses a lawn trampling behavior detection method based on a patrol robot, and comprises the following steps: controlling the patrol robot to move in a preset place and collecting image information of the preset place; obtaining lawn information in the image information by using a preset lawn semantic segmentation network; obtaining human body information in the image information by using a preset human body instance segmentation network; judging whether there is a lawn trampling behavior in the image information according to the lawn information and the human body information; and if there is, outputting human body information of a person who tramples on the lawn. The application effectively solves the problems of missed detection, false detection and slow detection speed in the prior art when detecting the lawn trampling behavior.

This invention discloses a method, system, electronic device, and storage medium for identifying obstructed fire lanes. The method includes: a robot patrolling a fire lane area within a patrol environment; the robot is equipped with a camera; acquiring captured information within the fire lane area, including images and video streams; pushing the captured information to a backend, and using deep learning methods to analyze and judge the captured information to detect whether vehicles appear in the captured information; detecting vehicles appearing in the captured information, and processing the detection results using a tracking algorithm based on time sequence to determine the vehicle's bounding box and the type of vehicle being tracked; and judging the vehicle's status based on the vehicle's bounding box and vehicle type to determine whether the vehicle is illegally parked and obstructing the fire lane. This invention's method for identifying obstructed fire lanes reduces labor costs while improving efficiency, greatly enhancing the timeliness and safety of the overall solution.

An apparatus and method for removing weeds from an aesthetic mulch garden using an autonomous battery-powered differential-wheeled robot is disclosed. The boundary of the domain of said aesthetic mulch garden is predefined by the user and said robot is confined to patrol within said domain. The robot searches for weeds using machine vision which seeks colorimetric contrast between weeds and mulch and undergoes a novel randomized reflective trajectory to patrol said domain. An independent collision avoidance system allows said robot to avoid interaction with non-weed objects. Said robot has a central processing unit (CPU) receiving input from said machine vision system which positions a device for weed extraction and controls said extraction. A built-in suction system and receptacle is incorporated in said robot to maintain the weed extraction device clean and ready for operation while storing extracted weeds for later disposal.

The application discloses a door and window opening and closing detection method and device based on robot inspection, a medium and equipment, comprising collecting reference images and to-be-detected images of detection points based on a patrol robot; aligning the to-be-detected images with the reference images, performing background difference, and obtaining a foreground target binary image; performing image processing on the foreground target binary image, and obtaining a suspicious area frame; mapping the suspicious area frame to the reference images and the aligned to-be-detected images, respectively obtaining reference areas and to-be-detected areas; performing feature extraction on the reference areas and the to-be-detected areas, respectively obtaining reference area image feature vectors and to-be-detected area image feature vectors; calculating cosine similarity of the two image feature vectors; judging whether a door and window is opened or not according to the cosine similarity, and generating door and window opening and closing information. The application effectively overcomes the problems of high modification cost and low detection robustness in door and window opening and closing detection, and greatly improves the application generalization of door and window opening and closing detection.

The invention discloses a patrol robot voice interaction system with environment perception capability, which is characterized by comprising an environment voiceprint modeling module, an acoustic interference recognition module, an instruction double confirmation module, a semantic coupling verification module, a confidence coefficient dynamic adjustment module and an instruction behavior consistency filtering module, an environment voiceprint real-time extraction module with a frequency domain redundancy analysis mechanism is constructed, environment acoustic signals on a patrol path are continuously collected, and a frequency band mapping vector is constructed based on the collected acoustic signals. The method has the advantages that the voice false triggering risk in the high-noise environment can be accurately recognized, and the recognition robustness is improved through semantic verification and a dual-confirmation mechanism; meanwhile, by combining confidence coefficient dynamic adjustment and behavior consistency filtering, context rationality judgment of the control instruction is achieved, and it is ensured that instruction execution is safe and reliable.

The invention is suitable for the technical field of artificial intelligence, and provides an event discovery method based on a patrol robot, and the method comprises the steps: obtaining a historical discovery event of a target region, the historical event comprising an event type, an event discovery time, and an event discovery place; based on the event type, the event discovery time and the event discovery place, constructing an event discovery matrix corresponding to the historical discovery event; taking the residence time of the patrol robot in each statistical area, the patrol speed of the patrol robot and the accessibility of the patrol robot as constraint conditions, taking the maximum event discovery probability of a predetermined event and the event discovery efficiency as a target function, and constructing a route optimization model of the multi-target patrol robot; and outputting an optimized patrol route of at least one patrol robot through the route optimization model of the multi-target patrol robot, and controlling the at least one patrol robot to execute the optimized patrol route for event discovery.

1. The name of the design product: patrol robot. 2. The use of the design product: for security patrol. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view.

This invention relates to the field of data processing, specifically to an interactive patrol robot intelligent agent system based on a large language model. The system includes a terminal interaction layer, a cloud decision-making layer, and a robot execution layer. The terminal interaction layer receives natural language commands or shortcut commands input by the user and sends them to the cloud decision-making layer. It also receives and displays task execution status and result information returned by the cloud decision-making layer. The cloud decision-making layer, deployed on a cloud server, receives user command information from the terminal interaction layer, robot status information and task execution result information from the robot execution layer, and pre-stored patrol scene map information. It uses a large language model to perform semantic understanding and logical reasoning on multi-source heterogeneous data, converting the user's natural language commands into standardized command data packages executable by the robot, and then sends them to the robot execution layer.