Robot control method and system for intelligent garbage collection in residential district

Abstract

The invention provides a robot control method and system for intelligent garbage collection in a residential district, and relates to the technical field of intelligent robos.The method comprises the steps that a garbage collection instruction is received, and the instruction comprises garbage classification types; according to the garbage classification type, the corresponding garbage robot is automatically awakened, and a collection task is prepared to be executed; after receiving the instruction, the robot selects a corresponding garbage can according to the garbage type; a corresponding walking route is planned by utilizing a built-in path planning algorithm and combining real-time environment information; in the advancing process, real-time environment perception is achieved through a laser radar and a visual module, and collision is avoided. The functions of garbage classified collection, real-time environment perception, safety monitoring and alarming, linkage with an access control and elevator system, automatic returning and cleaning and the like are achieved in an automatic and intelligent mode, the garbage collection efficiency, accuracy and safety are improved, and meanwhile the user experience and the environmental sanitation level of a community are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent robots, and in particular to a robot control method and system for intelligent garbage collection in residential areas. Background Art

[0002] Traditional garbage collection mainly relies on manual operations, including garbage collection, classification, and transportation, which is not only time-consuming and labor-intensive, but also inefficient. As the amount of garbage continues to increase, the labor costs required continue to rise, bringing a heavy economic burden to property management. During the manual garbage collection process, it is easy to cause problems such as garbage scattering and odor diffusion, which pollutes the community environment and affects the quality of life of residents. Especially in hot weather or when garbage has been piled up for a long time, the problem is more serious.

[0003] Due to the limitations of manual sorting, garbage sorting is often not accurate enough, resulting in recyclables, hazardous waste, etc. not being properly handled, wasting resources and potentially causing long-term harm to the environment. During manual garbage collection, workers need to frequently come into contact with garbage, which poses safety risks such as being stabbed by sharp objects and being infected with germs. At the same time, traffic accidents may also occur during the driving of garbage trucks, posing a threat to personnel safety.

[0004] Traditional garbage collection methods lack intelligent management and monitoring methods, and cannot provide real-time information on the status of garbage collection, overflow of garbage bins, and the work progress of staff. This leads to inefficient management and difficulty in responding to and handling problems in a timely manner. As the size of communities, residents' living habits, and garbage sorting policies change, traditional garbage collection methods are unable to quickly adapt to these changes. For example, adjustments to garbage sorting standards may require retraining of staff, increasing management difficulty and costs. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a robot control method and system for intelligent garbage collection in residential areas, which improves the efficiency, accuracy and safety of garbage collection.

[0006] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0007] In a first aspect, a robot control method for intelligent garbage collection in a residential area, the method comprising:

[0008] Receive a garbage collection instruction, which includes the type of garbage classification;

[0009] According to the type of garbage classification, the corresponding garbage robot is automatically awakened to prepare for the collection task;

[0010] After receiving the instruction, the robot selects the corresponding trash bin according to the type of garbage;

[0011] The built-in path planning algorithm is used in combination with real-time environmental information to plan the corresponding walking route. During the journey, the laser radar and vision module are used to achieve real-time environmental perception and avoid collisions.

[0012] Before the robot arrives at the unit building, it communicates with the access control and elevator system through the access control and elevator control module; controls the access control to open and allow the robot to enter the building; controls the elevator to enable the robot to reach the designated floor; while moving in the building, it continues to use the security monitoring module to monitor the environmental safety in real time. If any abnormal situation is found, it connects to the community security system through wireless communication to realize immediate alarm;

[0013] After the robot reaches the owner's floor, it sends a door-opening notification to the owner through the communication reminder module; after the owner opens the door, he puts the garbage into the classified garbage bin carried by the robot; after the robot confirms that the garbage has been collected, it closes the garbage bin cover and prepares to return;

[0014] The robot returns to the centralized garbage recycling center along the original route; during the return process, it uses the automatic obstacle avoidance module and the safety monitoring module to ensure safe travel; after arriving at the centralized garbage recycling center, it starts the garbage sorting and dumping module to accurately identify and classify the garbage according to the garbage classification information; after the garbage sorting and dumping is completed, the robot enters the automatic flushing area for cleaning; after cleaning, the robot returns to the standby state and waits for the next task instruction.

[0015] Furthermore, the built-in path planning algorithm is used in combination with real-time environmental information to plan the corresponding walking route; during the journey, the laser radar and vision module are used to achieve real-time environmental perception and avoid collisions, including:

[0016] The robot builds a real-time environment model that includes static and dynamic obstacles based on the floor information in the task instruction, combined with the map data and real-time environment information in the community;

[0017] Based on the environment model, the robot uses the built-in path planning function to calculate the final walking route from the current location to the target floor by searching and evaluating various paths;

[0018] During the movement, the lidar and vision modules continue to work, scanning the surrounding environment, identifying obstacles, and adjusting the route in real time to avoid collisions.

[0019] Furthermore, the calculation formula for the final walking route from the current location to the target floor is:

[0020]

[0021] Among them, p *represents the final walking route from the current location to the target floor; P(S,G) represents the set of all possible paths from the starting location S to the target location G; α, β, γ, δ, η represent weight coefficients; L(p) represents the length of path p; d min (p) represents the distance to the nearest obstacle on path p; ∈ represents a positive number; T(p) represents the number of turns on path p; H(p) represents the number of times path p crosses the high-risk area; n represents the total number of small segments into which path p is divided; F i represents the force that the robot needs to overcome on the i-th segment; Δs i Indicates the length of the i-th segment; i represents the index variable.

[0022] Furthermore, before the robot arrives at the unit building, it communicates with the access control and elevator system through the access control and elevator control module; controls the access control to open, allowing the robot to enter the building; controls the elevator to run, so that the robot can reach the designated floor; while moving in the building, it continues to use the security monitoring module to monitor the environmental safety in real time. If an abnormal situation is found, it connects to the community security system through wireless communication to realize immediate alarm, including:

[0023] Before the robot arrives at the unit building, it communicates with the access control system through the built-in access control and elevator control module to send a door opening request;

[0024] After the access control system passes the verification, the access control will be automatically opened to allow the robot to enter the building;

[0025] After entering the building, the robot establishes communication with the elevator system, sends the target floor information to the elevator system, and requests the elevator to reach the specified floor;

[0026] When the elevator reaches the designated floor, the robot walks out of the elevator and starts the in-building travel mode. At the same time, the safety monitoring module starts to monitor the safety status of the surrounding environment in real time.

[0027] The robot uses the built-in positioning system and sensor data to obtain the current position, target position and environmental obstacle information, and plans the next movement path based on the current position, target position and environmental obstacle information;

[0028] During the robot's movement, the safety monitoring module continuously monitors the environment, including fire, intrusion, and obstacle abnormalities. If an abnormal situation occurs, the safety monitoring module sends an alarm message to the community security system, including the type, location, and time information of the abnormal situation.

[0029] Furthermore, after the robot reaches the owner's floor, it sends a door-opening notification to the owner through the communication reminder module; after the owner opens the door, he puts the garbage into the classified garbage bin carried by the robot; after the robot confirms that the garbage has been collected, it closes the garbage bin cover and prepares to return, including:

[0030] The robot uses its internal navigation system to determine that it has reached the target floor and is ready to perform the garbage collection task. It also uses the communication reminder module to send a door opening request containing identity verification information to the owner.

[0031] The owner opens the door after verifying his identity and puts the sorted garbage into the robot's trash bin;

[0032] The robot enters the trust region mode to evaluate whether the garbage is correctly placed in the bin and uses sensors, including weight sensors and cameras, to monitor the status of the bin;

[0033] According to the preset garbage classification and collection standards, the robot sets a target state, that is, the type and amount of garbage contained in the trash can, and continuously evaluates the difference between the current state and the target state within the trust domain through the difference function; when it is determined that the garbage is correctly placed in the trash can, the robot closes the trash can lid, updates the internal state, marks that the garbage collection task has been completed, and prepares to return to the centralized garbage recycling center.

[0034] Furthermore, the calculation formula of the difference function is:

[0035]

[0036] Where D(C,Y) represents the difference between the current trash bin state C and the target state Y; N represents the number of types of trash; j represents the index variable; U j represents the weight coefficient of the jth type of garbage; C j represents the number of the jth type of garbage currently in the trash bin; Y j represents the number of j-th type of garbage that should be achieved; τ j represents the adjustment coefficient; c j The characteristic vector representing the current state of the j-th type of garbage; y j The characteristic vector representing the j-th garbage target state; represents the penalty coefficient; a represents the total capacity limit of the trash bin.

[0037] Furthermore, the robot returns to the centralized garbage collection center along the original route; during the return process, the automatic obstacle avoidance module and the safety monitoring module are used to ensure the safety of the movement; after arriving at the centralized garbage collection center, the garbage classification dumping module is activated to accurately identify and classify the garbage according to the garbage classification information; after the garbage classification dumping is completed, the robot enters the automatic flushing area for cleaning; after cleaning, the robot returns to the standby state and waits for the next task instruction, including:

[0038] The robot receives the instruction to return to the centralized garbage collection center and starts to return along the original route according to the path information;

[0039] The automatic obstacle avoidance module uses sensors to monitor the obstacles around the robot in real time. When an obstacle is identified, the robot automatically adjusts its route to avoid it. At the same time, the safety monitoring module continuously monitors the robot's speed, battery power, and motor temperature indicators.

[0040] After the robot arrives at the centralized garbage collection center, it starts the garbage classification and dumping process. The robot uses built-in sensors to identify the types of garbage in the garbage bin, sorts different types of garbage, and dumps the sorted garbage into the corresponding recycling areas.

[0041] After completing the classification and dumping of garbage, turn off the garbage classification and dumping module and enter the cleaning program; the robot moves to the preset automatic flushing area and is cleaned and flushed. After cleaning, it moves out of the flushing area and returns to the standby state, waiting for the next task instruction.

[0042] In a second aspect, a robot control system for intelligent garbage collection in a residential area comprises:

[0043] A robot body module, configured with a mobile device and at least one garbage collection box to perform a garbage collection task;

[0044] The environmental monitoring and perception module is installed on the robot body and is used to monitor the type, quantity and overflow status of garbage in the garbage collection box in real time, and to sense surrounding obstacles, pedestrians and vehicles;

[0045] The positioning and path planning module is used to determine the robot's position in the residential area and plan the final garbage collection route based on real-time information;

[0046] The communication and remote control module is used to establish communication with the intelligent terminals and property management center in the community to realize data transmission, command reception and remote monitoring functions;

[0047] The control and task execution module is used to perform garbage collection, sorting, transportation and obstacle avoidance tasks based on input information from sensors, positioning systems and communication systems;

[0048] The user interaction and command input module is provided on the robot body and is used to display the garbage collection status and the robot working status to the user and provide an input interface for the user's operation commands;

[0049] The energy management and automatic charging module is used to monitor the battery power of the robot in real time and automatically charge it when the power is low.

[0050] According to a third aspect, a computing device includes:

[0051] one or more processors;

[0052] The storage device is used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method described.

[0053] In a fourth aspect, a computer-readable storage medium stores a program, and when the program is executed by a processor, the method described is implemented.

[0054] The above solution of the present invention includes at least the following beneficial effects:

[0055] By receiving garbage collection instructions containing garbage classification types and automatically waking up the corresponding garbage robot, rapid response and efficient execution of garbage collection are achieved. This method shortens the time of garbage collection and improves overall work efficiency. The robot selects the corresponding garbage bin according to the type of garbage, and accurately identifies and classifies the garbage for dumping at the centralized garbage recycling center, ensuring the accuracy and effectiveness of garbage classification, which is conducive to the recycling of resources and environmental protection. Using laser radar and vision modules for real-time environmental perception, combined with path planning algorithms, the robot can autonomously plan walking routes and avoid collisions, improving the safety and reliability of the garbage collection process.

[0056] The robot can automatically communicate with the access control and elevator systems to control the opening of the access control and the operation of the elevator without human intervention, thus realizing the full automation and intelligence of garbage collection. At the same time, it is connected to the community security system through wireless communication to realize instant alarm and enhance the security of the community. After the robot reaches the owner's floor, it sends a door opening notification to the owner through the communication reminder module, making it convenient for the owner to put out the garbage. This humanized design improves user satisfaction and participation, making the garbage collection process more convenient and efficient.

[0057] Intelligent garbage collection robots have replaced traditional manual garbage collection methods, reducing labor costs. At the same time, the robot has self-monitoring and fault warning functions, which can detect and deal with potential problems in a timely manner, reducing maintenance costs. Through accurate garbage classification and garbage recycling and reuse, it helps to reduce the pollution of landfill and incineration to the environment and promote the recycling and sustainable development of resources. At the same time, the robot's automatic flushing function also ensures its long-term cleanliness and hygiene. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flow chart of a robot control method for intelligent garbage collection in a residential area provided by an embodiment of the present invention.

[0059] Figure 2 It is a schematic diagram of a robot control system for intelligent garbage collection in a residential area provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0061] like Figure 1 As shown, an embodiment of the present invention provides a robot control method for intelligent garbage collection in a residential area, the method comprising the following steps:

[0062] Step 11, receiving a garbage collection instruction, the instruction including the garbage classification type;

[0063] Step 12: According to the garbage classification type, the corresponding garbage robot is automatically awakened to prepare for the collection task;

[0064] Step 13, after receiving the instruction, the robot selects the corresponding trash bin according to the type of trash;

[0065] Step 14: Use the built-in path planning algorithm and real-time environmental information to plan a corresponding walking route; during the walking process, use the laser radar and vision module to achieve real-time environmental perception and avoid collisions;

[0066] Step 15, before the robot arrives at the unit building, it communicates with the access control and elevator system through the access control and elevator control module; controls the access control to open, allowing the robot to enter the building; controls the elevator to run, so that the robot can reach the designated floor; while moving in the building, it continues to use the security monitoring module to monitor the environmental safety in real time. If any abnormal situation is found, it connects to the community security system through wireless communication to realize immediate alarm;

[0067] Step 16: After the robot reaches the owner's floor, it sends a door-opening notification to the owner through the communication reminder module; after the owner opens the door, he puts the garbage into the classified garbage bin carried by the robot; after the robot confirms that the garbage has been collected, it closes the garbage bin cover and prepares to return;

[0068] Step 17, the robot returns to the garbage collection center along the original route; during the return process, the automatic obstacle avoidance module and the safety monitoring module are used to ensure the safety of the movement; after arriving at the garbage collection center, the garbage classification and dumping module is started to accurately identify and classify the garbage according to the garbage classification information; after the garbage classification and dumping is completed, the robot enters the automatic flushing area for cleaning; after cleaning, the robot returns to the standby state and waits for the next task instruction.

[0069] In an embodiment of the present invention, by receiving instructions containing specific garbage classification types, the system can immediately clarify the goals and priorities of the collection task, which helps to improve the pertinence and effectiveness of garbage collection and reduce unnecessary waste of resources. Automatically waking up a specific robot according to the garbage classification type achieves optimal allocation and efficient utilization of resources. This on-demand scheduling mechanism can ensure that each garbage robot is fully utilized while avoiding idleness and waste of resources. The robot can quickly select the corresponding garbage bin according to the garbage type information in the instruction, which helps to achieve preliminary classification and collection of garbage. The robot can autonomously plan and optimize the walking route while effectively avoiding collisions and obstacles. This not only improves the efficiency of garbage collection, but also ensures the safe operation of the robot. The robot can autonomously communicate with the access control and elevator systems and control their operation, achieving seamless shuttle and garbage collection in the building. At the same time, the real-time monitoring and instant alarm functions of the security monitoring module ensure the safe operation of the robot in the building, providing additional security for community residents.

[0070] The communication reminder module sends door opening notifications to the owner, achieving effective communication with the owner. The owner can conveniently put out the garbage, and the robot can quickly and accurately complete the garbage collection task. This humanized design improves user satisfaction and participation. The robot can safely return to the centralized garbage recycling center along the original route, and quickly start the garbage classification and dumping module after arriving to accurately classify and dump. This not only improves the efficiency and quality of garbage disposal, but also reduces manual intervention and errors. At the same time, the setting of the automatic flushing area ensures the cleanliness and hygiene of the robot, making it fully prepared for the execution of the next task. The efficient and automated operation of the entire process greatly reduces labor and maintenance costs.

[0071] In a preferred embodiment of the present invention, the above step 11, receiving a garbage collection instruction, the instruction including the garbage classification type; the above step 12, automatically waking up the corresponding garbage robot according to the garbage classification type to prepare to perform the collection task; the above step 13, after the robot receives the instruction, selecting the corresponding garbage bin according to the garbage type, may include:

[0072] In an embodiment of the present invention, the server of the garbage collection system continuously monitors garbage collection requests from the owner's mobile phone APP, smart home system or property management platform. When a request arrives, the receiving module immediately captures the request and preliminarily verifies its format and validity. The received instruction is passed to the parsing module, which is responsible for parsing the instruction content and extracting key information, including the type of garbage classification (such as recyclables, kitchen waste, hazardous waste, etc.). The parsing module uses JSON, XML or a custom protocol to parse the instruction data. The parsed instruction information is stored in the database. At the same time, according to the type of garbage classification, the instructions are distributed to the corresponding garbage robot control queue, waiting to be processed. The system may send a confirmation message to the owner, indicating that the instruction has been received and is being processed. This message can be sent in the form of a push notification, text message or email from a mobile phone APP.

[0073] In step 12, the system queries the list of currently available garbage robots based on the type of garbage classification in the instruction. The selection logic considers the robot's current status (such as whether it is online, whether it has sufficient power, whether it is performing other tasks, etc.), location information, and garbage classification capabilities. The system sends a wake-up signal to the selected robot via the wireless network, which contains the task instructions and necessary configuration information. After receiving the wake-up signal, the robot switches from standby or sleep state to working state, ready to perform the collection task. The robot loads the task instructions and performs initialization settings based on the type of garbage classification in the instruction. This includes selecting an appropriate garbage bin, configuring the path planning algorithm, starting the environmental perception module, etc. The robot sends a status update message to the system indicating that it is ready to perform the task. The system updates the robot's status information and provides real-time feedback to the owner or property management party when necessary.

[0074] Step 13, after receiving the task instruction from the system, the robot first parses and extracts the garbage classification type and other relevant information. The robot is equipped with one or more garbage bins, each of which corresponds to one or more types of garbage. According to the analyzed garbage classification type, the robot uses internal selection logic to determine which garbage bin should be used. The robot installs the selected garbage bin into the collection device through the robotic arm. After the garbage bin is installed, the robot performs necessary checks to ensure that the garbage bin is secure and well sealed. The robot sends a status confirmation message to the system, indicating that the garbage bin has been correctly installed and is ready to collect garbage. The system updates the robot's status information and provides further feedback or guidance to the owner or property management party when necessary.

[0075] In a preferred embodiment of the present invention, the above step 14 uses the built-in path planning algorithm and real-time environmental information to plan a corresponding walking route; during the walking process, the laser radar and vision module are used to realize real-time environmental perception and avoid collision, which may include:

[0076] Step 141, the robot builds a real-time environment model including static and dynamic obstacles according to the floor information in the task instruction, combined with the map data and real-time environment information in the community;

[0077] Step 142, based on the environment model, the robot uses the built-in path planning function to calculate the final walking route from the current location to the target floor by searching and evaluating various paths;

[0078] Step 143, during the moving process, the laser radar and vision module continue to work, scan the surrounding environment, identify obstacles, and adjust the moving route in real time to avoid collisions.

[0079] In an embodiment of the present invention, the robot first receives a task instruction and extracts the target floor information. At the same time, the robot accesses the map database in the community to obtain static information such as the overall layout of the community, floor distribution, channel width, etc. The robot also receives real-time environmental information through a wireless communication module, such as the location of other robots, moving pedestrians, temporary obstacles and other dynamic information. The robot uses the acquired data to build a real-time environmental model containing static and dynamic obstacles. In the model, static obstacles such as walls and pillars are represented in a fixed manner; dynamic obstacles such as pedestrians and other robots are updated according to real-time information. The robot continuously receives new real-time environmental information and continuously updates the environmental model to ensure its accuracy.

[0080] Step 142, the robot first loads the constructed environment model, which contains the static layout of the community (such as corridors, walls, elevator locations, etc.) and dynamic obstacle information (such as pedestrians, other robots, temporary obstacles, etc.). The robot determines its current position through a built-in positioning system (such as GPS, RFID, SLAM, etc.). Set the target floor as the end point of the path planning. Create an open list (Open List) to store the path nodes to be evaluated. Create a closed list (Closed List) to store the path nodes that have been evaluated to avoid repeated evaluation. Take the current position of the robot as the starting node, add it to the open list, and set its cost to 0. Select the node with the lowest cost from the open list as the current node, remove it from the open list, and add it to the closed list. Check whether the current node is the target floor node. If so, the path search is completed and the loop is exited. If not, continue with the following steps. According to the position of the current node, find all possible neighbor nodes (that is, nodes that can be reached directly from the current node) in the environment model. For each neighbor node, calculate its cost (usually including the path length from the starting point to the node, the additional cost caused by obstacle density, the number of turns, etc.). For each neighbor node, check whether it is already in the closed list. If it is, ignore it. If it is not in the closed list, calculate the total cost Q = X + A from the starting point through the current node to the neighbor node, and add it to the open list. Among them, X is the actual path cost from the starting point to the current node, and then through the current node to the neighbor node; A represents the heuristic cost estimate from the neighbor node to the target node. If the neighbor node is already in the open list, but the newly calculated total cost is lower, update the cost and parent node information of the node.

[0081] When the target floor node is found, the path search is complete. Starting from the target floor node, by tracking the parent node information of each node, the final path from the starting point to the target floor is reversely constructed. The robot stores the final path in memory. Based on the path information, the robot adjusts its own direction and speed and prepares to follow the route. During the journey, the robot will fine-tune the path based on real-time environmental information (such as new obstacles) to ensure safe arrival at the target floor.

[0082] Step 143, while the robot is moving, the laser radar and vision module continue to work and scan the surrounding environment. The laser radar identifies obstacles by emitting laser beams and receiving reflected signals, and calculates their distance and position. The vision module uses a camera to capture environmental images and identifies obstacles through image processing algorithms. When the robot detects an obstacle ahead, it immediately adjusts the route according to the location and size of the obstacle. Adjustments include deceleration, steering, detours, and other actions to ensure that the robot can safely avoid obstacles.

[0083] Suppose a robot needs to collect garbage from a garbage collection point in one corner of a community to the 10th floor of a building in another corner. The robot first obtains a map of the community to understand the overall layout. Then, it obtains real-time information such as the location of other robots and pedestrian flow through wireless communication. Finally, it combines this information to build an environmental model that contains static (such as walls, stairs) and dynamic (such as pedestrians, other robots) obstacles. The robot uses a path planning algorithm to search for all possible paths from the garbage collection point to the target floor in the environmental model. After evaluation, a route that is short and avoids peak traffic is selected. The route includes passing through a garden, bypassing a building, and taking the elevator to the 10th floor.

[0084] During the journey, the robot's lidar detected a pedestrian crossing the path ahead, and the vision module confirmed this. The robot immediately adjusted its route, slowed down, turned slightly, safely bypassed the pedestrian, and then continued along the original route.

[0085] Through path planning algorithms and real-time environmental perception, the robot is able to select the optimal path and adjust it in real time, thereby improving the efficiency of garbage collection. The real-time obstacle avoidance function of the LiDAR and vision module ensures that the robot can safely avoid obstacles during the journey, avoiding collisions and damage. The robot can intelligently plan routes and avoid obstacles, reducing user complaints and dissatisfaction caused by the robot getting lost or colliding. By reducing collisions and damage, the service life of the robot is extended, thereby reducing maintenance costs. The intelligent path planning and obstacle avoidance technology of the garbage collection robot provides reference and reference for robot applications in other fields, and promotes the development of intelligent technology.

[0086] In a preferred embodiment of the present invention, the calculation formula for the final walking route from the current location to the target floor is:

[0087]

[0088] Among them, p * represents the final walking route from the current location to the target floor; P(S,G) represents the set of all possible paths from the starting location S to the target location G; α, β, γ, δ, η represent weight coefficients; L(p) represents the length of path p; d min (p) represents the distance to the nearest obstacle on path p; ∈ represents a positive number; T(p) represents the number of turns on path p; H(p) represents the number of times path p crosses the high-risk area; n represents the total number of small segments into which path p is divided; F i represents the force that the robot needs to overcome on the i-th segment; Δs i Indicates the length of the i-th segment; i represents the index variable.

[0089] In an embodiment of the present invention, a starting position S and a target position G (i.e., the target floor) are determined. Initialize weight coefficients α, β, γ, δ, and η, which are used to balance the importance of different factors in path selection. Set a positive number ∈ to avoid the situation where the denominator is zero when calculating the distance to the nearest obstacle. Initialize an empty set P(S, G) to store all possible paths from the starting position S to the target position G. Using a path planning algorithm (such as the A* algorithm), search for all possible paths from the starting position S to the target position G in the environmental model and add them to the set P(S, G). Ensure that each path is completely and accurately represented, including information such as the length of the path, turning points, and distance to obstacles.

[0090] For each path P in the set P(S,G), perform the following steps:

[0091] Use a distance metric (such as Euclidean distance) to calculate the total length L(p) of path P. Traverse each point on path p, calculate the distance from the point to the nearest obstacle, and take the minimum value as d min (p). Add a positive number ∈ to avoid the denominator being zero. Count the number of turns on path p, including right-angle turns, sharp-angle turns, etc. According to the definition of high-risk areas in the environment model, count the number of times path p crosses these areas. Divide path p into n small segments. For each small segment i, calculate the force F that the robot needs to overcome i and the length of the small segment Δs i . Use the given formula to calculate the total cost of path p Traverse all paths in the set P(S,G) and find the path p with the minimum total cost * . * As the final walking route from the current location to the target floor.

[0092] The path length, distance to the nearest obstacle, number of turns, number of times crossing high-risk areas, and the force required to overcome on the path can comprehensively evaluate the quality of the path. By adjusting the weight coefficients α, β, γ, δ, and η, each factor can be weighed according to actual needs and scene characteristics to find the most suitable walking route. The term takes into account the distance between the path and the nearest obstacle, so that the robot can stay as far away from obstacles as possible during walking, reducing the risk of collision and jamming. The term δ×H(p) takes into account the number of times the path crosses high-risk areas. By reducing the number of times it crosses high-risk areas, the probability of robot failure or damage can be reduced. α×L(p) takes into account the length of the path, so that the robot can choose the shortest path to reach the destination and improve walking efficiency. The term γ×T(p) takes into account the number of turns on the path. By reducing the number of turns, the robot's energy consumption and walking time can be reduced.

[0093] The term takes into account the forces that need to be overcome in each small section of the path, which enables the robot to choose a more labor-saving walking route in complex environments (such as ramps, stairs, etc.). By comprehensively considering multiple factors, this formula can be applied to various complex scenarios and environments, improving the adaptability and flexibility of the robot. The optimized walking route can reduce the robot's walking time and energy consumption, and improve the user's efficiency. At the same time, by avoiding unexpected situations such as collisions and jams, it can also improve the user's trust and satisfaction with the robot.

[0094] In a preferred embodiment of the present invention, in the above step 15, before the robot arrives at the unit building, it communicates with the access control and elevator system through the access control and elevator control module; controls the access control to open, allowing the robot to enter the building; controls the elevator to run, so that the robot can reach the designated floor; while moving in the building, continues to use the security monitoring module to monitor the environmental safety in real time, and if an abnormal situation is found, connects to the community security system through wireless communication to realize immediate alarm, which may include:

[0095] Step 151, the robot arrives in front of the unit building and communicates with the access control system through the built-in access control and elevator control module to send a door opening request;

[0096] Step 152, after the access control system passes the verification, the access control is automatically opened to allow the robot to enter the building;

[0097] Step 153, after entering the building, the robot establishes communication with the elevator system, sends the target floor information to the elevator system, and requests the elevator to reach the designated floor;

[0098] Step 154, after the elevator reaches the designated floor, the robot walks out of the elevator and starts the in-building travel mode. At the same time, the safety monitoring module is started to monitor the safety status of the surrounding environment in real time;

[0099] Step 155, the robot uses the built-in positioning system and sensor data to obtain the current position, target position and environmental obstacle information, and plans the next moving path according to the current position, target position and environmental obstacle information;

[0100] Step 156, during the robot's movement, the security monitoring module continuously monitors the environment, including fire, intrusion, and obstacle abnormalities. If an abnormal situation occurs, the security monitoring module sends an alarm message to the community security system, including the type, location, and time information of the abnormal situation.

[0101] In the embodiment of the present invention, the built-in access control and elevator control module of the robot is activated, and a communication connection is established with the access control system through a wireless or wired network (such as Wi-Fi, Bluetooth, Zigbee, RS485, etc.). The robot sends a door opening request data packet containing the robot's identity authentication information to the access control system. The data packet may contain the robot's ID, password, access rights, etc. After receiving the request, the access control system verifies the robot's identity, including comparing the robot ID, checking access rights, etc.

[0102] Step 152: After the access control system verifies the robot's identity, it sends a door opening command to the access control device (such as an electromagnetic lock, electric door, etc.). After receiving the door opening command, the access control device automatically unlocks or opens, allowing the robot to enter the building. The robot uses sensors (such as infrared sensors, ultrasonic sensors, etc.) to detect whether the access control is fully opened, and after confirming that it is correct, it enters the building through the access control.

[0103] Step 153, after the robot enters the building, the built-in access control and elevator control module automatically searches and establishes a communication connection with the elevator system. The robot sends a request data packet containing the target floor information to the elevator system. The data packet may contain the number of the target floor, the robot ID, etc. After receiving the request, the elevator system plans and executes the operation task to the target floor according to the robot's request and the current elevator operation status.

[0104] Step 154: After the elevator reaches the designated floor, it sends an arrival signal to the robot. After receiving the signal, the robot controls the elevator door to open and walks out of the elevator. The robot starts the in-building travel mode, adjusts the travel speed and direction, and prepares to travel in the building. At the same time, the robot's safety monitoring module is activated, and the safety status of the surrounding environment is monitored in real time through cameras, infrared sensors, smoke sensors, etc.

[0105] Step 155, the robot uses the built-in positioning system (such as GPS, UWB, laser navigation, etc.) and sensor data (such as infrared sensor, ultrasonic sensor, etc.) to obtain the current position, target position and environmental obstacle information. Based on the information obtained, the robot uses a path planning algorithm (such as A* algorithm) to plan the next moving path to ensure that it can reach the target position safely and efficiently.

[0106] Step 156, during the robot's movement, the security monitoring module continuously monitors the environment, captures image information through the camera, and detects abnormal conditions such as fire, intrusion, and obstacles through infrared sensors, smoke sensors, etc. If an abnormal condition is found, the security monitoring module immediately sends an alarm message to the community security system. The alarm message includes the type of abnormal condition (such as fire, intrusion, obstacle, etc.), location (such as floor, room number, etc.), and time information (such as occurrence time, duration, etc.). After receiving the alarm message, the community security system immediately takes corresponding measures, such as notifying security personnel to go to the scene to handle it, activating the emergency plan, etc.

[0107] Take a delivery robot in a certain community as an example. The robot needs to deliver items from the community gate to the designated floor of a certain building. When the robot arrives in front of the unit building, it first communicates with the access control system through the built-in access control and elevator control module and sends a door opening request. After the access control system verifies the identity of the robot, it automatically opens the access control and allows the robot to enter the building. Then, the robot establishes communication with the elevator system, sends the target floor information to the elevator system, and requests the elevator to reach the designated floor. After the elevator arrives, the robot walks out of the elevator, starts the in-building travel mode, and starts the safety monitoring module to monitor the environment in real time. During the travel process, the robot uses the positioning system and sensor data to plan the movement path and successfully avoids obstacles. Suddenly, the safety monitoring module detects that smoke is coming out of a room, and a fire may have occurred. The robot immediately sends an alarm message to the community security system, including the type of fire, room location, and time of occurrence. After receiving the alarm, the community security system immediately notifies the security personnel to go to the scene to handle it, and activates the emergency plan to ensure the safety of community residents.

[0108] The robot can automatically communicate with the access control and elevator systems, quickly enter the building and reach the designated floor, improving delivery efficiency. The robot's built-in safety monitoring module can monitor environmental safety in real time, detect and report abnormal situations in a timely manner, and enhance the safety of the community. The robot can complete delivery tasks autonomously, reducing the workload of community security and property personnel. The application of robots has improved the intelligence level of the community and provided residents with a more convenient and safe living environment. In the event of an abnormal situation, the robot can quickly send an alarm message to the community security system, improving the emergency response speed and helping to reduce losses and harm.

[0109] In a preferred embodiment of the present invention, the above step 16, after the robot reaches the owner's floor, sends a door opening notification to the owner through the communication reminder module; after the owner opens the door, the owner places the garbage into the classified garbage bin carried by the robot; after the robot confirms that the garbage has been collected, it closes the garbage bin cover and prepares to return, which may include:

[0110] Step 161, the robot determines through the internal navigation system that it has reached the target floor, is ready to perform the garbage collection task, and uses the communication reminder module to send a door opening request containing identity authentication information to the owner;

[0111] Step 162, the owner opens the door after verifying his identity and puts the sorted garbage into the robot's trash bin;

[0112] Step 163, the robot enters the trust region mode, evaluates whether the garbage is correctly placed in the garbage bin, and uses sensors, including weight sensors and cameras, to monitor the status of the garbage bin;

[0113] In step 164, the robot sets a target state, i.e., the type and amount of garbage contained in the trash bin, according to the preset garbage classification and collection standards, and continuously evaluates the difference between the current state and the target state within the trust domain through the difference function; when it is determined that the garbage is correctly placed in the trash bin, the robot closes the trash bin lid, updates the internal state, marks that the garbage collection task has been completed, and prepares to return to the centralized garbage recycling center.

[0114] In an embodiment of the present invention, the robot's internal navigation system uses technologies such as laser navigation, visual navigation or inertial navigation to locate and confirm that it has reached the target floor in real time. The robot is ready to perform the garbage collection task and activates the communication reminder module. The communication reminder module sends a door opening request to the owner's mobile phone, smart home system, etc. through a wireless network (such as Wi-Fi, Bluetooth) or a wired network. The request contains the robot's identity authentication information, such as the robot ID, access password or encrypted access token. After receiving the request, the owner's mobile phone or smart home system displays a door opening request notification and prompts the owner to authenticate the identity.

[0115] Step 162, the owner verifies his identity by entering an access password, scanning a QR code, or performing facial recognition. After successful identity verification, the owner opens the door and allows the robot to enter. The owner puts the pre-sorted garbage (such as recyclables, hazardous waste, wet garbage, dry garbage, etc.) into the classified garbage bin carried by the robot. The robot detects through a sensor (such as an infrared sensor) that the owner has put out the garbage and is ready to proceed to the next step.

[0116] Step 163, the robot enters the trust domain mode, in which the robot will more strictly evaluate whether the garbage is correctly placed in the trash can according to the classification standards. The robot uses a camera to capture the inside of the trash can and uses image recognition technology to determine whether the garbage is correctly classified. At the same time, the robot uses a weight sensor to measure the weight change of the trash can to evaluate whether the garbage has been placed. The robot also uses other sensors (such as ultrasonic sensors) to monitor whether the lid of the trash can is closed and whether there is a foreign object stuck.

[0117] Step 164, the robot sets a target state according to the preset garbage classification and collection standards, that is, the standard that the types and quantities of garbage contained in the garbage bin should meet. The robot continuously evaluates the difference between the current state (such as the type, quantity, weight, etc. of garbage in the garbage bin) and the target state within the trust domain through the difference function. When the difference function evaluation result meets the preset conditions, that is, the garbage has been correctly placed in the garbage bin according to the classification standards, the robot closes the garbage bin cover. The robot updates the internal state, marks that the garbage collection task has been completed, and prepares to return to the garbage collection center for further processing.

[0118] Taking a smart community as an example, the robot arrives at a certain owner's floor according to the predetermined plan to perform the garbage collection task. After the robot confirms that it has reached the target floor through the internal navigation system, it uses the communication reminder module to send a door opening request to the owner. After the owner receives the request through the mobile phone APP, he enters the access password for identity authentication. After the identity authentication is successful, the owner opens the door and puts the sorted garbage (such as recyclable paper, plastic bottles, etc.) into the robot's classified garbage bin. The robot enters the trust domain mode, uses the camera and weight sensor to monitor the status of the garbage bin, and evaluates the difference between the current state and the target state through the difference function. After confirming that the garbage has been correctly placed, the robot closes the garbage bin lid, updates the internal state to "garbage collection task completed", and prepares to return to the garbage collection center for the next step of processing.

[0119] The robot can automatically reach the owner's floor and perform garbage collection tasks, reducing the time and cost of manual garbage collection and improving garbage collection efficiency. The robot evaluates whether the garbage is correctly placed in the garbage bin according to the classification standards through the trust region model and difference function, which helps to ensure the accuracy of garbage classification. The application of robots has improved the intelligence level of the community and provided owners with more convenient and efficient garbage disposal services. The application of the robot garbage collection system helps to promote garbage classification and environmental awareness and encourage owners to actively participate in garbage classification. The robot can complete the garbage collection task independently, reducing the workload of property or cleaning staff and reducing labor costs. At the same time, it also avoids problems such as inaccurate or missed garbage classification caused by human factors.

[0120] In a preferred embodiment of the present invention, the calculation formula of the difference function is:

[0121]

[0122] Where D(C,Y) represents the difference between the current trash bin state C and the target state Y; N represents the number of types of trash; j represents the index variable; U j represents the weight coefficient of the jth type of garbage; C j represents the number of the jth type of garbage currently in the trash bin; Yj represents the number of j-th type of garbage that should be achieved; τ j represents the adjustment coefficient; c j The characteristic vector representing the current state of the j-th type of garbage; y j The characteristic vector representing the j-th garbage target state; represents the penalty coefficient; a represents the total capacity limit of the trash bin.

[0123] In the embodiment of the present invention, the number of types of garbage N is determined. A weight coefficient U is set for each type of garbage. j , which is often determined based on factors such as the importance of the garbage, the difficulty of handling it, or its recycling value. Set the adjustment coefficient τ j , used to adjust the relative importance of quantity differences and feature differences in the difference function. Determine the total capacity limit a of the garbage bin. Set the penalty coefficient Used to impose penalties for exceeding bin capacity.

[0124] The robot's sensors (such as weight sensors, cameras, etc.) are used to obtain the quantity C of each type of garbage in the current trash bin. j According to the preset garbage classification and collection standards, determine the amount Y that each type of garbage target should reach j For the characteristic vector c j and j , can be obtained through the preset standard value. For each type of garbage, calculate the current quantity C j With the target quantity Y j The absolute difference between |C j -Y j |. Calculate the current state characteristic vector c j and the target state feature vector y j The cosine similarity between Use the adjustment factor τ j Adjusts the contribution of feature differences in the difference function.

[0125] For each type of garbage, calculate the sum of its weighted quantity difference and characteristic difference, and sum them up to get a part of the total difference. If the total amount of garbage in the current garbage bin exceeds the capacity limit a, then according to the penalty coefficient The total difference and the penalty term are added together to get the final difference degree D(C,Y). According to the calculated difference degree D(C,Y), the difference between the current state of the trash bin and the target state is evaluated. If the difference degree is small, it means that the garbage has been correctly placed in the trash bin according to the classification standard; if the difference degree is large, further processing is required (such as reminding the owner to reclassify, the robot trying to adjust the garbage, etc.).

[0126] The difference function comprehensively considers the difference in quantity and characteristics of garbage, and uses the weight coefficient U j and adjustment factor τ j The setting of can flexibly adjust the importance of different types of garbage in the difference calculation, thereby ensuring the accuracy of garbage classification. The introduction of the characteristic vector enables the difference function to more finely reflect the state of the garbage, such as shape, material, etc., further improving the precision of garbage classification. By calculating the degree of difference, the robot can quickly determine whether the garbage in the trash can meets the preset collection standards, and thus decide whether to proceed to the next step, such as closing the trash can lid, returning to the garbage collection center, etc. This reduces the interaction time between the robot and the owner and improves the overall efficiency of garbage collection. The penalty term in the difference function It ensures that the trash bin will not be overloaded, thus avoiding robot operation failure or safety hazards caused by overloading. This helps to optimize the use of the trash bin, extend its service life, and reduce the additional maintenance costs caused by overloading. Accurate garbage classification and efficient garbage collection reduce the waiting time and operation complexity of the owner, and improve the user experience. The robot can give clear feedback based on the calculation results of the difference function, such as whether the garbage has been correctly classified and whether a certain type of garbage needs to be replenished, so that the owner can participate in the garbage classification work more easily. Accurate garbage classification helps to recycle and reuse resources and reduce environmental pollution caused by landfill and incineration. By optimizing the garbage collection process, energy consumption and carbon emissions are reduced, and environmental protection and sustainable development are promoted. The application of the difference function makes the garbage classification and collection process more intelligent and automated, providing strong support for the construction of smart communities and smart cities. This helps to improve the level of refinement of urban management, improve resource utilization efficiency, and promote the development of cities in a more green, intelligent and sustainable direction.

[0127] In a preferred embodiment of the present invention, in the above step 17, the robot returns to the garbage collection center along the original route; during the return process, the automatic obstacle avoidance module and the safety monitoring module are used to ensure the travel safety; after arriving at the garbage collection center, the garbage classification dumping module is started to accurately identify and classify the garbage according to the garbage classification information; after the garbage classification dumping is completed, the robot enters the automatic flushing area for cleaning; after the cleaning is completed, the robot returns to the standby state and waits for the next task instruction, which may include:

[0128] Step 171, the robot receives an instruction to return to the garbage collection center, and starts to return along the original route according to the path information;

[0129] Step 172, the automatic obstacle avoidance module monitors the obstacles around the robot in real time through sensors. When an obstacle is identified, the robot automatically adjusts its route to avoid the obstacle. At the same time, the safety monitoring module continuously monitors the robot's speed, battery power, and motor temperature indicators.

[0130] Step 173, after the robot arrives at the garbage collection center, it starts the garbage classification and dumping program; the robot identifies the types of garbage in the garbage bin through the built-in sensor, sorts the different types of garbage, and dumps the sorted garbage into the corresponding recycling areas;

[0131] Step 174, after completing the classified dumping of garbage, turn off the classified dumping module and enter the cleaning program; the robot moves to the preset automatic flushing area, cleans and flushes the robot, and after completing the cleaning, moves out of the flushing area, returns to the standby state, and waits for the next task instruction.

[0132] In the embodiment of the present invention, the robot receives a return instruction from the central control system through the wireless communication module, and the instruction includes the return path information. The robot plans the optimal return route based on the received path information, using the built-in map data and path planning algorithm. The robot starts the motor and drive wheels according to the planned route and starts to return to the garbage collection center along the original route.

[0133] Step 172, the sensors in the automatic obstacle avoidance module (such as ultrasonic sensors, infrared sensors, laser radars, etc.) transmit signals to the surroundings in real time and receive reflected signals to monitor the obstacles around the robot. Based on the received signal strength and time difference, the automatic obstacle avoidance module calculates the distance and direction of the obstacle and identifies the obstacle to be avoided. When an obstacle is identified, the robot automatically adjusts the route according to the obstacle avoidance algorithm to avoid the obstacle while maintaining the travel speed and direction. The safety monitoring module monitors the robot's speed, battery power, motor temperature and other indicators in real time to ensure the safety of the robot during movement.

[0134] Step 173, the robot determines whether it has arrived at the garbage collection center through the built-in positioning module and map data. When it is confirmed to have arrived, the robot starts the garbage classification dumping program and prepares to dump the garbage by classification. The robot identifies the types of garbage in the garbage bin through built-in sensors (such as cameras, weight sensors, etc.). Based on the identification results, the robot controls the garbage classification dumping module to sort out different types of garbage and dump them into the corresponding recycling areas.

[0135] Step 174, the robot determines whether the garbage has been completely dumped through sensors and internal logic. When it is confirmed that the dumping is complete, the robot turns off the garbage classification dumping module and stops the dumping operation. The robot moves to the preset automatic flushing area and prepares for cleaning. The robot starts the cleaning program and uses the water spray device and the brushing device to clean and flush the robot to remove the dirt and garbage residue attached to the surface of the robot. After cleaning is completed, the robot moves out of the flushing area and returns to the standby area or designated location. The robot enters the standby state and waits for the next task instruction sent by the central control system.

[0136] Assume that the robot is performing a garbage sorting and recycling task. After completing the garbage sorting and collection on a certain floor, it needs to return to the garbage collection center for dumping and cleaning. The robot receives the return instruction and plans the final return route based on the previously recorded path information and starts to return along the original route. During the robot's movement, the robot detects an obstacle in front of it (such as a parked bicycle) through the ultrasonic sensor. The robot immediately adjusts its route and bypasses the obstacle. At the same time, the safety monitoring module monitors the robot's various safety indicators in real time to ensure safe movement. After the robot arrives at the garbage collection center, it starts the garbage sorting and dumping program. The camera identifies the types of garbage in the garbage bin, such as recyclables and hazardous waste, and controls the dumping module to dump different types of garbage into the corresponding recycling area. After completing the classified dumping of the garbage, the robot turns off the dumping module and moves to the automatic washing area for cleaning. The robot is fully cleaned by the water spray device and the scrubbing device to remove the dirt and garbage residue attached to the surface of the robot. After cleaning, the robot moves out of the washing area and returns to the standby area to wait for the next task instruction.

[0137] Through built-in sensors and garbage classification and dumping programs, the robot can accurately identify and classify garbage for dumping, improving the accuracy of garbage classification. The robot can automatically return to the centralized garbage recycling center for dumping and cleaning, optimizing the garbage recycling process and improving recycling efficiency. The application of automatic obstacle avoidance module and safety monitoring module ensures the safety of the robot during the movement process and avoids collisions and failures. The application of automatic flushing area enables the robot to perform comprehensive cleaning after completing garbage classification and dumping, maintaining the cleanliness and hygiene of the robot. The robot can automatically complete operations such as garbage classification, dumping and cleaning, reducing manual intervention and waiting time, and improving the utilization rate and work efficiency of the robot. Accurate garbage classification and efficient garbage recycling contribute to the recycling and reuse of resources, reduce environmental pollution, and promote environmental protection and sustainable development.

[0138] like Figure 2 As shown, an embodiment of the present invention also provides a robot control system for intelligent garbage collection in a residential area, comprising:

[0139] A robot body module, configured with a mobile device and at least one garbage collection box to perform a garbage collection task;

[0140] The environmental monitoring and perception module is installed on the robot body and is used to monitor the type, quantity and overflow status of garbage in the garbage collection box in real time, and to sense surrounding obstacles, pedestrians and vehicles;

[0141] The positioning and path planning module is used to determine the robot's position in the residential area and plan the final garbage collection route based on real-time information;

[0142] The communication and remote control module is used to establish communication with the intelligent terminals and property management center in the community to realize data transmission, command reception and remote monitoring functions;

[0143] The control and task execution module is used to perform garbage collection, sorting, transportation and obstacle avoidance tasks based on input information from sensors, positioning systems and communication systems;

[0144] The user interaction and command input module is provided on the robot body and is used to display the garbage collection status and the robot working status to the user and provide an input interface for the user's operation commands;

[0145] The energy management and automatic charging module is used to monitor the battery power of the robot in real time and automatically charge it when the power is low.

[0146] It should be noted that the system is a system corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0147] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A robot control method for intelligent garbage collection in residential areas, characterized in that: The method comprises: Receive a garbage collection instruction, which includes the type of garbage classification; According to the type of garbage classification, the corresponding garbage robot is automatically awakened to prepare for the collection task; After receiving the instruction, the robot selects the corresponding trash bin according to the type of garbage; The built-in path planning algorithm is used in combination with real-time environmental information to plan the corresponding walking route. During the journey, the laser radar and vision module are used to achieve real-time environmental perception and avoid collisions. Before the robot arrives at the unit building, it communicates with the access control and elevator system through the access control and elevator control module; controls the access control to open and allow the robot to enter the building; controls the elevator to enable the robot to reach the designated floor; while moving in the building, it continues to use the security monitoring module to monitor the environmental safety in real time. If any abnormal situation is found, it connects to the community security system through wireless communication to realize immediate alarm; After the robot reaches the owner's floor, it sends a door-opening notification to the owner through the communication reminder module; after the owner opens the door, he puts the garbage into the classified garbage bin carried by the robot; after the robot confirms that the garbage has been collected, it closes the garbage bin cover and prepares to return; The robot returns to the centralized garbage recycling center along the original route; during the return process, it uses the automatic obstacle avoidance module and the safety monitoring module to ensure safe travel; after arriving at the centralized garbage recycling center, it starts the garbage sorting and dumping module to accurately identify and classify the garbage according to the garbage classification information; after the garbage sorting and dumping is completed, the robot enters the automatic flushing area for cleaning; after cleaning, the robot returns to the standby state and waits for the next task instruction.

2. The robot control method for intelligent garbage collection in residential areas according to claim 1 is characterized in that: Use the built-in path planning algorithm and real-time environmental information to plan the corresponding walking route; During the driving process, the laser radar and vision module are used to achieve real-time environmental perception and avoid collisions, including: The robot builds a real-time environment model that includes static and dynamic obstacles based on the floor information in the task instruction, combined with the map data and real-time environment information in the community; Based on the environment model, the robot uses the built-in path planning function to calculate the final walking route from the current location to the target floor by searching and evaluating various paths; During the movement, the lidar and vision modules continue to work, scanning the surrounding environment, identifying obstacles, and adjusting the route in real time to avoid collisions.

3. The robot control method for intelligent garbage collection in residential areas according to claim 2 is characterized in that: The calculation formula for the final walking route from the current location to the target floor is: Among them, p * represents the final walking route from the current location to the target floor; P(S,G) represents the set of all possible paths from the starting location S to the target location G; α, β, γ, δ, η represent weight coefficients; L(p) represents the length of path p; d min (p) represents the distance to the nearest obstacle on path p; ∈ represents a positive number; T(p) represents the number of turns on path p; H(p) represents the number of times path p crosses the high-risk area; n represents the total number of small segments into which path p is divided; F i represents the force that the robot needs to overcome on the i-th segment; Δs i Indicates the length of the i-th segment; i represents the index variable.

4. The robot control method for intelligent garbage collection in residential areas according to claim 3 is characterized in that: Before the robot arrives at the unit building, it communicates with the access control and elevator system through the access control and elevator control module; controls the access control to open and allow the robot to enter the building; controls the elevator to enable the robot to reach the designated floor; while moving in the building, it continues to use the security monitoring module to monitor the environmental safety in real time. If any abnormal situation is found, it connects to the community security system through wireless communication to realize immediate alarm, including: Before the robot arrives at the unit building, it communicates with the access control system through the built-in access control and elevator control module to send a door opening request; After the access control system passes the verification, the access control will be automatically opened to allow the robot to enter the building; After entering the building, the robot establishes communication with the elevator system, sends the target floor information to the elevator system, and requests the elevator to reach the specified floor; When the elevator reaches the designated floor, the robot walks out of the elevator and starts the in-building travel mode. At the same time, the safety monitoring module starts to monitor the safety status of the surrounding environment in real time. The robot uses the built-in positioning system and sensor data to obtain the current position, target position and environmental obstacle information, and plans the next movement path based on the current position, target position and environmental obstacle information; During the robot's movement, the safety monitoring module continuously monitors the environment, including fire, intrusion, and obstacle abnormalities. If an abnormal situation occurs, the safety monitoring module sends an alarm message to the community security system, including the type, location, and time information of the abnormal situation.

5. The robot control method for intelligent garbage collection in residential areas according to claim 4 is characterized in that: After the robot reaches the owner's floor, it sends a door opening notification to the owner through the communication reminder module; After the owner opens the door, he / she places the garbage into the classified garbage bin carried by the robot; after the robot confirms that the garbage has been collected, it closes the lid of the garbage bin and prepares to return, including: The robot uses its internal navigation system to determine that it has reached the target floor and is ready to perform the garbage collection task. It also uses the communication reminder module to send a door opening request containing identity verification information to the owner. The owner opens the door after verifying his identity and puts the sorted garbage into the robot's trash bin; The robot enters the trust region mode to evaluate whether the garbage is correctly placed in the bin and uses sensors, including weight sensors and cameras, to monitor the status of the bin; According to the preset garbage classification and collection standards, the robot sets a target state, that is, the type and amount of garbage contained in the trash can, and continuously evaluates the difference between the current state and the target state within the trust domain through the difference function; when it is determined that the garbage is correctly placed in the trash can, the robot closes the trash can lid, updates the internal state, marks that the garbage collection task has been completed, and prepares to return to the centralized garbage recycling center.

6. The robot control method for intelligent garbage collection in residential areas according to claim 5, characterized in that: The calculation formula of the difference function is: Where D(C,Y) represents the difference between the current trash bin state C and the target state Y; N represents the number of types of trash; j represents the index variable; U j represents the weight coefficient of the jth type of garbage; C j represents the number of the jth type of garbage currently in the trash bin; Y j represents the number of j-th type of garbage that should be achieved; τ j represents the adjustment coefficient; c j The characteristic vector representing the current state of the j-th type of garbage; y j The characteristic vector representing the j-th garbage target state; represents the penalty coefficient; a represents the total capacity limit of the trash bin.

7. The robot control method for intelligent garbage collection in residential areas according to claim 6, characterized in that: The robot returns to the centralized garbage collection center along the original route; during the return process, the automatic obstacle avoidance module and the safety monitoring module are used to ensure safe travel; after arriving at the centralized garbage collection center, the garbage classification and dumping module is activated to accurately identify and classify the garbage according to the garbage classification information; after the garbage classification and dumping is completed, the robot enters the automatic flushing area for cleaning; After cleaning, the robot returns to standby mode and waits for the next task instruction, including: The robot receives the instruction to return to the centralized garbage collection center and starts to return along the original route according to the path information; The automatic obstacle avoidance module uses sensors to monitor the obstacles around the robot in real time. When an obstacle is identified, the robot automatically adjusts its route to avoid it. At the same time, the safety monitoring module continuously monitors the robot's speed, battery power, and motor temperature indicators. After the robot arrives at the centralized garbage collection center, it starts the garbage classification and dumping process. The robot uses built-in sensors to identify the types of garbage in the garbage bin, sorts different types of garbage, and dumps the sorted garbage into the corresponding recycling areas. After completing the classification and dumping of garbage, turn off the garbage classification and dumping module and enter the cleaning program; the robot moves to the preset automatic flushing area and is cleaned and flushed. After cleaning, it moves out of the flushing area and returns to the standby state, waiting for the next task instruction.

8. A robot control system for intelligent garbage collection in a residential area, the system implementing the method as claimed in any one of claims 1 to 7, characterized in that: include: A robot body module, configured with a mobile device and at least one garbage collection box to perform a garbage collection task; The environmental monitoring and perception module is installed on the robot body and is used to monitor the type, quantity and overflow status of garbage in the garbage collection box in real time, and to sense surrounding obstacles, pedestrians and vehicles; The positioning and path planning module is used to determine the robot's position in the residential area and plan the final garbage collection route based on real-time information; The communication and remote control module is used to establish communication with the intelligent terminals and property management center in the community to realize data transmission, command reception and remote monitoring functions; The control and task execution module is used to perform garbage collection, sorting, transportation and obstacle avoidance tasks based on input information from sensors, positioning systems and communication systems; The user interaction and command input module is provided on the robot body and is used to display the garbage collection status and the robot working status to the user and provide an input interface for the user's operation commands; The energy management and automatic charging module is used to monitor the battery power of the robot in real time and automatically charge it when the power is low.

9. A computing device, characterized in that include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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