Remote control response method and device based on positioning and storage medium

Abstract

The invention discloses a positioning-based remote control response method and device and a storage medium, and belongs to the technical field of positioning. The method is applied to the golf trolley and comprises the steps of obtaining first positioning data through a positioning module, receiving second positioning data sent by a remote controller, calculating relative position information with the remote controller based on a differential correction algorithm according to the first positioning data and the second positioning data, and calling the golf trolley on the basis of the relative position information after a calling request of the remote controller is received. And generating a response path in the court map, and moving according to the response path to respond to the calling request. According to the method, the relative position information is calculated through complementarity of the double-source positioning data, so that the generated response path has higher space consistency in the court map coordinate system, and the safety risk possibly encountered in the movement process of the golf bag vehicle based on the response path is avoided.

Description

Technical Field

[0001] The present application relates to the field of positioning technology, and in particular to a positioning-based remote control response method, device, and storage medium. Background Art

[0002] The golf bag car can respond to the user's call through the remote control, obtain the current positioning information through the navigation system, plan the path to the user according to the positioning information, and complete the response to the user's remote control.

[0003] However, due to cost constraints, the low-cost Global Positioning System (GPS) modules used in golf carts in related technologies lack accurate positioning, with errors typically exceeding two meters. Consequently, the golf cart navigation system cannot generate a reliable path that stays within the safe distance of the golf course's restricted area boundary, making it prone to violations when the golf carts follow the planned path.

[0004] The above content is only used to assist in understanding the technical solution of this application and does not constitute an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a positioning-based remote control response method, device and storage medium, aiming to solve the technical problem that when the positioning accuracy of the golf bag car is low, it is easy to trigger violations when moving based on the planned path.

[0006] To achieve the above objectives, the present application provides a positioning-based remote control response method, the method comprising the following steps: Acquire first positioning data through the positioning module and receive second positioning data sent by the remote control; Calculating relative position information between the golf bag car and the remote controller based on the first positioning data and the second positioning data using a differential correction algorithm; After receiving the call request from the remote controller, generating a response path in the course map based on the relative position information; Move according to the response path to respond to the summon request.

[0007] In one embodiment, the step of calculating the relative position information of the golf bag car and the remote controller based on the first positioning data and the second positioning data using a differential correction algorithm includes: Extracting the pseudorange and carrier phase from the first positioning data and the second positioning data within a preset time window; Determining an initial baseline vector based on the pseudorange, and determining the number of integer cycles of the carrier phase through an ambiguity fixing algorithm; Iterating the initial baseline vector based on the integer cycle number and the carrier phase to obtain a baseline vector; The relative position information is determined based on the baseline vector, the first positioning data, and the second positioning data.

[0008] In one embodiment, after the step of calculating the relative position information of the golf bag car and the remote controller based on the first positioning data and the second positioning data using a differential correction algorithm, the method further includes: When an interruption of the first positioning data and / or the second positioning data is detected, acquiring corresponding inertial sensor data; performing dead reckoning based on the inertial sensor data to generate displacement compensation data; The displacement compensation data is integrated into the calculation result of the differential correction algorithm to update the relative position information.

[0009] In one embodiment, the step of moving according to the response path to respond to the summon request includes: Obtaining a cost map and determining a cost value for a grid in the cost map; Determining a safe area in the course map according to the cost value; The response path is locally adjusted according to the safety area, and movement is performed according to the adjusted response path.

[0010] In one embodiment, before the steps of obtaining a cost map and determining the cost value of a grid in the cost map, the process further includes: Retrieving the course map, and obtaining static obstacle information and area information from the map semantic information of the course map; rasterizing the course map to obtain a rasterized map; The cost value is assigned to a grid in the rasterized map according to the static obstacle information and the region information to obtain the cost map.

[0011] In one embodiment, before the step of locally adjusting the response path according to the security area and moving according to the adjusted response path, the method further includes: Collect the environmental image of the golf cart through the camera; Segmenting the environment image using a semantic segmentation model to identify image feature information; Comparing the image feature information with the course map, and correcting the map deviation according to the comparison result; The safety area is updated based on the correction result of the map deviation.

[0012] In one embodiment, after the step of moving according to the response path to respond to the summon request, the method further includes: Determining the relative distance of the remote controller based on the real-time relative position information; When the relative distance is less than a preset distance, identifying the target point in the environment image captured by the camera through a semantic segmentation model; Determine a target point position corresponding to the target point; The docking position is adjusted according to the target point position, and the vehicle is moved to the docking position.

[0013] In one embodiment, after the step of moving according to the response path to respond to the summon request, the method further includes: In the stadium map, determining the boundaries of the penalty area; When the distance between the first positioning data and the restricted area boundary is less than a safety distance threshold, triggering emergency braking; An action of replanning the response path is executed.

[0014] In addition, to achieve the above-mentioned purpose, the present application also provides a positioning-based remote control response device, which includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program is configured to implement the steps of the positioning-based remote control response method as described above.

[0015] In addition, to achieve the above-mentioned purpose, the present application also provides a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the positioning-based remote control response method as described above are implemented.

[0016] One or more technical solutions proposed in this application have at least the following technical effects: This application uses a differential correction algorithm to fuse the golf cart's own positioning data with the positioning data sent by the remote control, thereby calculating relative position information based on the complementarity of the dual-source positioning data. This overcomes the defect of large errors in the single positioning source of low-cost positioning modules, making the generated response path have higher spatial consistency in the course map coordinate system, and avoiding the risk of path deviation caused by absolute positioning errors. At the same time, this application dynamically modifies the path by combining the course's cost map and visual module. Compared with traditional solutions that rely on single low-precision positioning data, the reliability of path planning is improved, so that the golf cart can maintain an effective position association with the remote control when responding to a call, and can also maintain a compliant and safe distance from the restricted area boundary based on the course's geographic information constraints, achieving the dual technical effects of balancing cost control and safety regulations. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a flow chart of the first embodiment of the positioning-based remote control response method of the present application; Figure 2 This is a flow chart of the second embodiment of the positioning-based remote control response method of the present application; Figure 3 This is a flowchart of the third embodiment of the positioning-based remote control response method of the present application; Figure 4 This is a flowchart of a fourth embodiment of the positioning-based remote control response method of the present application; Figure 5 This is a flowchart of the fifth embodiment of the positioning-based remote control response method of the present application; Figure 6 This is a flowchart of a sixth embodiment of the positioning-based remote control response method of the present application; Figure 7 It is a structural diagram of a positioning-based remote control response device in the hardware operating environment involved in the embodiment of the present application.

[0020] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0022] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0023] The main solution of the embodiment of the present application is: obtaining first positioning data through a positioning module and receiving second positioning data sent by a remote control; calculating relative position information with respect to the remote control based on a differential correction algorithm according to the first positioning data and the second positioning data; after receiving a call request from the remote control, generating a response path in a course map based on the relative position information; and moving according to the response path to respond to the call request.

[0024] Existing golf carts can respond to user calls via remote control, obtain current location information through a navigation system, and then plan a route to the user based on this location information to complete the response. However, due to cost considerations, the positioning accuracy of the low-cost Global Positioning System (GPS) modules used in golf carts is insufficient, with an error typically exceeding 2 meters. In this case, the golf cart navigation system cannot generate a reliable movement path that stays within the safe distance of the golf course's restricted area boundary, making it easy for the golf cart to trigger violations when moving along the planned movement path.

[0025] This application uses a differential correction algorithm to fuse the golf cart's own positioning data with the positioning data sent by the remote control, thereby calculating relative position information based on the complementarity of the dual-source positioning data. This overcomes the defect of large errors in the single positioning source of low-cost GPS modules, making the generated response path have higher spatial consistency in the course map coordinate system, and avoiding the risk of path deviation caused by absolute positioning errors. At the same time, this application dynamically modifies the path by combining the course's cost map and visual module. Compared with traditional solutions that rely on single low-precision positioning data, the reliability of path planning is improved, so that the golf cart can maintain an effective position association with the remote control when responding to a call, and can also maintain a compliant and safe distance from the restricted area boundary based on the course's geographic information constraints, achieving the dual technical effects of balancing cost control and safety regulations.

[0026] To better understand the above technical solutions, exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0027] It should be noted that the execution subject of this embodiment can be a golf cart, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, etc., or an electronic device capable of implementing the above functions, a positioning-based remote control response device, etc., and this embodiment does not specifically limit this. The following uses a golf cart as an example to illustrate this embodiment and the following embodiments.

[0028] Based on this, the embodiment of the present application provides a remote control response method based on positioning, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the positioning-based remote control response method of the present application.

[0029] In this embodiment, the positioning-based remote control response method includes steps S10 to S40: Step S10: obtaining first positioning data through the positioning module and receiving second positioning data sent by the remote control; In this embodiment, both the golf cart and the remote control are equipped with positioning modules that can receive GPS signals and identify current positioning data, thereby determining first positioning data and second positioning data. The first positioning data is the real-time positioning data of the golf cart, and the second positioning data is the real-time positioning data of the remote control. Furthermore, the golf cart receives the second positioning data sent by the remote control via the communication module, and based on the first and second positioning data, determines the differential data between the golf cart and the remote control.

[0030] Specifically, the scooter and remote controller utilize an existing remote control communication link, such as long-range radio (LoRa) for long-distance, low-power signal transmission, or wireless fidelity (Wi-Fi) for differential data transmission, ensuring bandwidth and latency meet real-time requirements. For example, the differential data rate is approximately 1 to 5 kbps. Data transmission is prioritized in descending order: differential signal, control command, and status feedback.

[0031] It should be noted that the carrier phase observation is the phase difference between the satellite carrier signal received by the GPS receiver and the reference carrier signal generated by the receiver's oscillator. In theory, the carrier phase observation is the instantaneous carrier phase value of the GPS signal at the moment of reception. However, in practice, it is impossible to directly measure the instantaneous carrier phase value of any signal. Instead, the phase difference between the received carrier signal with Doppler frequency shift and the reference carrier signal generated by the receiver is measured. After the GPS signal is received by the receiver, it first performs a pseudo-random code delay lock, thereby achieving tracking of the satellite signal. Once tracking is successful, the receiver's local pseudo-random code is strictly aligned with the satellite's pseudo-random code, providing a pseudo-range observation. A phase-locked loop (PLL) is then used to achieve phase lock. After phase lock, the phase of the receiver's local signal is identical to the phase of the GPS carrier signal. The difference between the receiver's local signal phase and the initial phase is the carrier phase observation.

[0032] Alternatively, due to wireless communication delays or packet loss, which can easily lead to differential correction failure, or insufficient computing power for the trolley control system to process vision and path planning in real time, the trolley control system uses a fragmented data transmission method and performs packet loss verification through a cyclic redundancy check (CRC), as well as enabling historical data interpolation in the event of packet loss. At the same time, the trolley control system can also use a higher-performance microcontroller unit (MCU) or split the task to the remote control end for calculation.

[0033] Step S20: Calculating relative position information between the golf bag car and the remote controller based on a differential correction algorithm according to the first positioning data and the second positioning data; In this embodiment, after the golf bag car obtains the first positioning data and receives the second positioning data, the golf bag car and the remote control can be used as base stations through a differential correction algorithm to calculate the relative position relationship between the golf bag car and the remote control to improve the positioning accuracy of the golf bag car.

[0034] For example, relying solely on low-cost GPS modules like the U-blox MAX-M10Q results in a large absolute positioning error, typically within a range of 2 to 5 meters. However, by using the dual GPS raw data from the caddy and remote control, such as pseudorange and carrier phase, exchanged in real time via wireless communication and employing methods such as baseline solution, the relative position between the two can be calculated. Without considering environmental interference, the relative error can be reduced to less than 1 meter. Pseudorange is the propagation time of the GPS satellite signal to the receiver multiplied by the speed of light. It is used to indicate the distance between the target to be located and the satellite and includes error information such as atmospheric delay and satellite clock error. Carrier phase is the number of carrier cycles of the GPS signal, and the number of whole cycles is usually determined using an ambiguity fixation algorithm.

[0035] Specifically, after receiving the first and second positioning data, the golf cart can eliminate the common error between the first and second positioning data through differential calculations. The golf cart can use single-difference processing to calculate the difference between the observation values ​​of the golf cart and the remote control for the same satellite, eliminating common errors such as satellite clock error and orbit error. Furthermore, the golf cart can use double-difference processing to further calculate the single-difference difference between two adjacent satellites to eliminate receiver clock error and ionospheric / tropospheric delay.

[0036] Furthermore, the golf cart control system can store the first positioning data and the second positioning data within a preset time window, and dynamically update the positioning data stored within the preset time window based on the first positioning data and the second positioning data acquired in real time. The golf cart control system can obtain the pseudorange and carrier phase from the first positioning data and the second positioning data.

[0037] As an optional implementation for calculating relative position information, the golf cart control system can preliminarily calculate the relative position and distance between the golf carts based on pseudoranges to determine the initial baseline vector. Simultaneously, an ambiguity fixation algorithm is used to determine the number of integer cycles of the carrier phase. For example, the ambiguity floating-point solution is estimated using the pseudorange wavelength. This is then combined with the least-squares descent correlation adjustment (LAMBDA) algorithm to search for the optimal integer solution, thereby fixing the floating-point solution to an integer.

[0038] Furthermore, the golf cart control system jointly solves the relative position of the golf cart and the remote control based on the pseudorange and carrier phase wave. Based on the integer number of cycles and the carrier phase, the golf cart control system can continuously iterate the initial baseline vector. The golf cart control system can calculate the residual value between the baseline vector of the current iteration and the observation value calculated by the carrier phase wave by the least square method, and complete the iteration to obtain the baseline vector when the residual value is less than the preset threshold. The baseline vector is used to describe the relative position relationship between two points in space and is represented by a three-dimensional coordinate difference. Based on the baseline vector, as well as the first positioning data and the second positioning data, the relative position information between the golf cart and the remote control can be determined.

[0039] Optionally, the ball bag car can also use pseudorange alone, or carrier phase wave alone, to calculate the residual value using the least squares method, thereby improving the accuracy of the position information by reducing the residual value, and determining the relative position information when the accuracy is less than a preset threshold.

[0040] Optionally, the golf bag car can also interact with the positioning base station based on the edge of the golf course, and the golf bag car and the remote control can interact with the positioning base station respectively to determine the first positioning data of the golf bag car and the second positioning data of the remote control respectively, so as to use the position relationship between the first positioning data and the second positioning data as a relative position relationship.

[0041] Step S30: after receiving the call request from the remote controller, generating a response path in the course map based on the relative position information; Step S40: moving according to the response path to respond to the summoning request.

[0042] In this embodiment, the response path is generated by combining relative position information with a course map to ensure the cart can safely and efficiently move to the target location. Upon receiving a call from the remote control, the cart control system initiates a path planning process to the remote control's corresponding location. Based on the relative position information and the course map stored in the system, the cart generates a response path and moves to the remote control's location based on this response path.

[0043] As an optional implementation, the golf cart's path planning can utilize a global path planning algorithm, such as the A* algorithm or the Recurrently Target-Attending Tracking (RTT) algorithm, to generate an initial path. Furthermore, based on this initial path, the golf cart can also utilize a dynamic window approach (DWA) to dynamically adjust the path locally to avoid dynamic obstacles.

[0044] The A* algorithm is an algorithm that finds the lowest cost path among multiple nodes on a graph plane, searching for the optimal path. The RTT algorithm is a single-query path planning algorithm that uses the root node as the search starting point and then randomly adds leaf nodes through sampling to generate a random expansion tree. When a newly sampled leaf node enters the target range, the path from the starting point to the target location is obtained.

[0045] As another alternative embodiment, the golf cart control system can use a cost map of the course map to determine the cost values ​​assigned to each barrier in the cost map based on obstacles and restricted areas. The subsequent path direction is determined based on the cost values ​​of the adjacent barriers at each barrier location in the path. The map describes the navigation cost of each location in the environment, and each location (i.e., each barrier) is assigned a different cost value, reflecting the relative difficulty of the golf cart moving in different areas.

[0046] Optionally, the golf cart control system can combine global path planning with restricted area constraints to generate an initial path. For example, the golf cart can use a cost map, combined with an RTT algorithm, to perform a weighted summation of the cost values ​​of adjacent fences at a certain location on the path, combined with the RTT algorithm path score, to connect the selected fences to form a complete path.

[0047] Optionally, the golf bag car is also equipped with a vision module, which can identify obstacles in the path, dynamically avoid obstacles and adjust the path.

[0048] The embodiment of the present application uses a differential correction algorithm to fuse the golf cart's own positioning data with the positioning data sent by the remote control, thereby calculating relative position information based on the complementarity of the dual-source positioning data. This overcomes the drawback of the large error of a single positioning source in low-cost GPS modules, allowing the generated response path to have higher spatial consistency in the course map coordinate system, thus avoiding the risk of path deviation caused by absolute positioning error. At the same time, the present application dynamically modifies the path by combining the course's cost map and visual module. Compared with traditional solutions that rely on single low-precision positioning data, the reliability of path planning is improved, allowing the golf cart to maintain an effective position association with the remote control when responding to a call, while maintaining a compliant and safe distance from the restricted area boundary based on the course's geographic information constraints, achieving the dual technical effects of balancing cost control and safety regulations.

[0049] Based on the same inventive concept, this application also provides a second embodiment, referring to Figure 2 , Figure 2 This is a flow chart of the second embodiment of the positioning-based remote control response method of the present application.

[0050] In this embodiment, after calculating the relative position information of the golf bag car and the remote controller based on the first positioning data and the second positioning data using a differential correction algorithm as described in step S20, steps S21 to S23 are further included: Step S21: when detecting that the first positioning data and / or the second positioning data are interrupted, acquiring corresponding inertial sensor data; Step S22: performing dead reckoning based on the inertial sensor data to generate displacement compensation data; Step S23: integrating the displacement compensation data into the calculation result of the differential correction algorithm to update the relative position information.

[0051] It should be noted that, further, due to the multipath effect of low-cost GPS, such as the reflection of signals from metal obstacles on the golf course, the positioning of the golf cart and the remote control will jump during the positioning process. At the same time, when both the golf cart and the remote control are moving, the differential algorithm is not stable enough for dynamic baseline solution. When the GPS signal is interrupted during the movement of the golf cart, the inertial sensor (IMU, Inertial Measurement Unit) can be used to estimate short-term displacement to compensate for positioning continuity.

[0052] Specifically, the golf cart control system is also equipped with an IMU sensor. When the golf cart fails to obtain the first positioning data and / or the second positioning data within a time period greater than a preset time period, or when the first positioning data and / or the second positioning data are detected to be interrupted, the golf cart control system determines that the GPS signal is interrupted and obtains the inertial sensor data within the corresponding time period. The purpose of dead reckoning is to estimate the displacement of the golf cart using the inertial sensor data when the GPS signal is interrupted, thereby ensuring the continuity of the relative position information. Although there are cumulative errors in the inertial sensor, it can provide an effective displacement estimate in a short time. Based on the inertial sensor data, the golf cart integrates the acceleration within the time period to obtain velocity information, and further integrates the velocity to calculate the corresponding displacement data. The displacement data is combined with the angular velocity information in the inertial sensor data to generate displacement compensation data. By integrating the displacement compensation data into the calculation results of the differential correction algorithm, the relative position information can be updated.

[0053] Optionally, the spherical vehicle can combine the raw GPS data with the angular velocity / acceleration information from the IMU and Inertial Measurement Unit, and the continuous inter-frame motion estimation of the visual odometry (VO), and perform spatiotemporal alignment and data fusion through the extended Kalman filter (EKF). The high-frequency dynamic response of the IMU and the relative pose constraints of the VO can be used to compensate for GPS signal distortion and smooth the positioning trajectory.

[0054] Optionally, the ball bag car can also use sliding window optimization (SWO) or factor graph optimization (FGO) for solution. By maintaining the time window of historical observation data or constructing a probabilistic graph model containing multi-time state nodes and constraint edges, the baseline vector and sensor bias parameters under multiple epochs are jointly optimized to suppress the nonlinear error accumulation problem in the dynamic baseline solution of dual mobile terminals, thereby improving positioning consistency in complex scenarios.

[0055] In an embodiment of the present application, the golf cart can use inertial sensor data for dead reckoning when the GPS signal is interrupted, and update relative position information through data fusion. This method solves the problem of positioning interruptions caused by unstable GPS signals. By combining inertial sensors and a differential correction algorithm, it ensures the continuity and stability of positioning, improving the golf cart's navigation capabilities in complex environments.

[0056] Since the system described in Example 2 of this application is the system used to implement the method of Example 1 of this application, those skilled in the art will be able to understand the specific structure and variations of the system based on the method described in Example 1 of this application, and therefore, no further description is given here. All systems used in the method of Example 1 of this application fall within the scope of protection to be provided by this application.

[0057] Based on the same inventive concept, this application also provides a third embodiment, referring to Figure 3 , Figure 3 This is a flowchart of the third embodiment of the positioning-based remote control response method of the present application.

[0058] In this embodiment, moving according to the response path as described in step S40 to respond to the summon request includes steps S41 to S43: Step S41: Obtain a cost map and determine the cost value of a grid in the cost map; Step S42: determining a safe area in the course map according to the cost value; Step S43: locally adjusting the response path according to the safety area, and moving according to the adjusted response path.

[0059] In this embodiment, the cost map is a data structure that rasterizes the map and assigns a cost value to each grid for path planning. The cost value of each grid represents the difficulty of passing through the grid. The lower the cost value, the easier it is to pass. The cost value is determined by information such as static obstacles, dynamic obstacles, and area type. Among them, the purpose of determining the safe area by the cost value is to ensure that the golf bag car avoids high-risk areas such as restricted areas and sand pits during driving and selects the optimal path. The golf bag car can determine the safe area based on the cost value in the cost map and combined with the static and dynamic obstacle information.

[0060] Furthermore, the golf cart can retrieve the course map and obtain static obstacle information and area information from the map semantics of the course map. The course map is rasterized to obtain a rasterized map. Based on the static obstacle information and area information, cost values ​​are assigned to the grids in the rasterized map to obtain a cost map.

[0061] Specifically, the ball bag car control system can prepare and save the cost map in advance based on map information and navigation data, determine the safe area therein to perform path planning actions, or combine actual positioning information as well as laser and visual sensors to determine the safe area and generate a cost map in the process of moving based on the response path to achieve dynamic obstacle avoidance. It can also dynamically adjust the cost value of the fence in the currently saved cost map during movement to complete the adjustment or replanning of the local path.

[0062] For example, the golf cart is pre-loaded with a high-precision semantic map of the golf course, such as roads, obstacle areas, and restricted areas, and combines real-time GPS positioning (5-meter error) to delineate safe areas, and dynamically avoid obstacles through rasterized maps and cost maps.

[0063] This embodiment of the application uses a cost map and a local adjustment algorithm to dynamically avoid obstacles and ensure safe navigation in complex environments. This method solves the problem of static maps being unable to adapt to dynamic environments. By dynamically adjusting the cost value and planning local paths, the golf cart's environmental adaptability and navigation efficiency are improved.

[0064] Since the system described in Example 3 of this application is the system used to implement the method of Example 1 of this application, those skilled in the art will be able to understand the specific structure and variations of the system based on the method described in Example 1 of this application, and therefore will not be described in detail here. All systems used in the method of Example 1 of this application fall within the scope of protection to be provided by this application.

[0065] Based on the same inventive concept, this application also provides a fourth embodiment, referring to Figure 4 , Figure 4 This is a flow chart of the fourth embodiment of the positioning-based remote control response method of the present application.

[0066] In this embodiment, if Figure 3 Before locally adjusting the response path according to the safety area and moving according to the adjusted response path in step S43, steps S51 to S54 are also included: Step S51: collecting an environmental image of the golf cart through a camera; Step S52: Segmenting the environment image using a semantic segmentation model to identify image feature information; Step S53: comparing the image feature information with the course map, and correcting the map deviation according to the comparison result; Step S54: updating the safety area based on the correction result of the map deviation.

[0067] In this embodiment, the golf cart can also collect images of the environment of the golf cart and identify image information through the configured camera and visual recognition module. The golf cart can segment the environment image through the visual semantic segmentation model, identify feature information in the image, and match the feature information with preset features, thereby identifying image feature information and other information in the picture. Optionally, the golf cart can use a U-net model for image segmentation, or use MobileNetV3 and / or DeepLabv3 and / or a lightweight model as a visual semantic segmentation to identify key areas such as road surfaces and sand pits to compensate for map deviations.

[0068] Specifically, the ball bag car control system loads a pre-trained semantic segmentation model, segments the collected environmental images, outputs semantic masks, and identifies road boundaries and obstacle areas based on the semantic masks.

[0069] For example, the golf cart control system first uses a global path planning algorithm such as A* or RRT, combined with a cost map, to generate an initial response path and control the golf cart to move based on this initial response path. During the movement, the golf cart control system uses a semantic segmentation model to identify environmental information on the path and uses local dynamic adjustment algorithms such as DWA to avoid temporary obstacles and ensure that the golf cart stays in the center and away from the restricted area.

[0070] Alternatively, if semantic segmentation fails due to lighting variations such as shade or backlighting, or if dynamic obstacles like pedestrians and other golf carts are not covered by the pre-set map, the golf cart can integrate infrared cameras to combat lighting interference. Furthermore, the golf cart control system deploys a small-sample incremental learning model to gradually adapt to changes in the golf course environment.

[0071] Optionally, the car records its trajectory and obstacles while driving, and updates the shared map through crowdsourcing, thus avoiding discrepancies between the preset map and the real environment, as well as miscalibration caused by visual semantic segmentation errors. The car only enables visual calibration at high confidence levels to avoid false corrections.

[0072] In an embodiment of the present application, the golf cart can use semantic segmentation and map comparison technology to dynamically correct map deviations, ensure that path planning is based on the latest environmental information, solve the problem of deviation between the preset map and the actual environment, and improve the accuracy of path planning and environmental adaptability through visual perception and map updates.

[0073] Since the system described in Example 4 of this application is the system used to implement the method of Example 1 of this application, those skilled in the art will be able to understand the specific structure and variations of the system based on the method described in Example 1 of this application, and therefore will not be described in detail here. All systems used in the method of Example 1 of this application fall within the scope of protection to be provided by this application.

[0074] Based on the same inventive concept, this application also provides a fifth embodiment, referring to Figure 5 , Figure 5 This is a flowchart of the fifth embodiment of the positioning-based remote control response method of the present application.

[0075] In this embodiment, the positioning-based remote control response method further includes steps S61 to S64: Step S61: determining the relative distance of the remote controller based on the real-time relative position information; Step S62: When the relative distance is less than a preset distance, identifying a target point in the environment image captured by the camera using a semantic segmentation model; Step S63: determining the target point position corresponding to the target point; Step S64: adjusting the docking position according to the target point position and moving to the docking position.

[0076] In this embodiment, when the golf cart reaches the vicinity of the remote control position, that is, less than the preset distance, when the golf cart determines that the current position is near the user, the golf cart can switch to the visual module for navigation to improve navigation accuracy.

[0077] In one embodiment, the golf cart can use a semantic segmentation model to identify feature information in an image and match this feature information with target point feature information to determine the feature point. The target point feature information can be pre-stored remote control image features or user image features. The preset distance is typically the distance at which the golf cart's vision module can accurately identify the user's features.

[0078] In another embodiment, the golf cart control system may also use a visual positioning module to identify markers in the environment image, such as markers on the remote control, to lock the target point.

[0079] For example, the ball bag car generates an initial response path through global path planning combined with a cost map, and avoids temporary obstacles through local dynamic adjustment to ensure that the driving is centered and within the restricted area distance. Near the destination, visual positioning such as AprilTag or ORB-SLAM is used to lock the target point to improve the accuracy of the response path terminal.

[0080] The embodiment of the present application achieves precise docking based on visual recognition and coordinate conversion when the golf cart approaches the remote control, thereby solving the problem that low-cost GPS cannot meet the precise docking requirements, and ensures the accuracy of the docking position through semantic segmentation and coordinate conversion.

[0081] Since the system described in Example 5 of this application is the system used to implement the method of Example 1 of this application, those skilled in the art will be able to understand the specific structure and variations of the system based on the method described in Example 1 of this application, and therefore will not be described in detail here. All systems used in the method of Example 1 of this application fall within the scope of protection to be provided by this application.

[0082] Based on the same inventive concept, this application also provides a sixth embodiment, referring to Figure 6 , Figure 6 This is a flow chart of the sixth embodiment of the positioning-based remote control response method of the present application.

[0083] In this embodiment, the positioning-based remote control response method further includes steps S71 to S73: Step S71: Determine the boundary of the restricted area in the stadium map; Step S72: triggering emergency braking when the distance between the first positioning data and the restricted area boundary is less than a safety distance threshold; Step S73: Execute the response path replanning action.

[0084] In this embodiment, geo-fencing is used to define restricted area boundaries using polygons or line segments. The cart detects the cart's position in real time using the polygonal geo-fencing. If the cart approaches the restricted area boundary and the distance from the restricted area boundary falls below a safety distance threshold, it triggers path replanning or emergency braking. Furthermore, the cart's control system incorporates a buffer zone in turning areas, dynamically adjusting the turning radius based on IMU angular velocity detection to avoid impacts caused by approaching the restricted area boundary.

[0085] Optionally, the golf cart can also switch to a low-speed mode when approaching a restricted area, and prompt an administrator or user to take over control of the golf cart through tactile feedback of the remote control, such as vibration.

[0086] The embodiment of the present application solves the problem that the golf bag cart may accidentally enter the restricted area by triggering emergency braking when approaching the restricted area and ensuring safe navigation through path replanning. The safety and reliability of navigation are improved through geographic fencing and dynamic path planning.

[0087] Since the system described in Example 6 of this application is the system used to implement the method of Example 1 of this application, those skilled in the art will be able to understand the specific structure and variations of the system based on the method described in Example 1 of this application, and therefore will not be described in detail here. All systems used in the method of Example 1 of this application fall within the scope of protection to be provided by this application.

[0088] The present application provides a positioning-based remote control response device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the positioning-based remote control response method in the above-mentioned embodiment 1.

[0089] Reference below Figure 7, which shows a schematic structural diagram of a positioning-based remote control response device suitable for implementing embodiments of the present application. The positioning-based remote control response device in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 7 The positioning-based remote control response device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0090] like Figure 7 As shown, the positioning-based remote control response device may include a processing device 1001 (e.g., a core processor, a graphics processor, etc.), which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1003 into a random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the positioning-based remote control response device. Processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems may be connected to I / O interface 1006: input device 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output device 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage device 1003 including, for example, a magnetic tape, hard disk, etc.; and communication device 1009. Communication device 1009 may allow the location-based remote control response device to communicate with other devices wirelessly or by wire to exchange data. While the figure illustrates a location-based remote control response device with various systems, it should be understood that implementation or presence of all illustrated systems is not required. More or fewer systems may alternatively be implemented or present.

[0091] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are performed.

[0092] The positioning-based remote control response device provided in this application, which utilizes the positioning-based remote control response method of the aforementioned embodiment, can resolve the technical problem that when a golf cart has low positioning accuracy and moves based on a planned path, it is easy to trigger violations. Compared with the prior art, the beneficial effects of the positioning-based remote control response device provided in this application are the same as those of the positioning-based remote control response method provided in the aforementioned embodiment. Other technical features of the positioning-based remote control response device are the same as those disclosed in the method of the aforementioned embodiment and are not further described here.

[0093] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0094] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0095] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, a computer program) stored thereon, wherein the computer-readable program instructions are used to execute the positioning-based remote control response method in the above embodiment.

[0096] The computer-readable storage medium provided herein may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including, but not limited to, wires, optical cables, radio frequency (RF), etc., or any suitable combination thereof.

[0097] The computer-readable storage medium may be included in the positioning-based remote control response device, or may exist independently without being incorporated into the positioning-based remote control response device.

[0098] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the positioning-based remote control response device, the positioning-based remote control response device: obtains first positioning data through a positioning module and receives second positioning data sent by the remote control; calculates relative position information with respect to the remote control based on the first positioning data and the second positioning data based on a differential correction algorithm; after receiving a call request from the remote control, generates a response path on a course map based on the relative position information; and moves according to the response path to respond to the call request.

[0099] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0100] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0101] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0102] The computer-readable storage medium provided in this application stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned positioning-based remote control response method. This computer-readable storage medium can address the technical issue of golf carts easily triggering violations when moving along a planned path when positioning accuracy is low. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the positioning-based remote control response method provided in the aforementioned embodiments, and are not further elaborated here.

[0103] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A remote control response method based on positioning, characterized in that: Applied to a golf bag cart, the method comprises the following steps: Acquire first positioning data through the positioning module and receive second positioning data sent by the remote control; Calculating relative position information between the golf bag car and the remote controller based on the first positioning data and the second positioning data using a differential correction algorithm; After receiving the call request from the remote controller, generating a response path in the course map based on the relative position information; Move according to the response path to respond to the summon request.

2. The method according to claim 1, wherein The step of calculating the relative position information between the golf bag car and the remote controller based on the first positioning data and the second positioning data using a differential correction algorithm includes: Extracting the pseudorange and carrier phase from the first positioning data and the second positioning data within a preset time window; Determining an initial baseline vector based on the pseudorange, and determining the number of integer cycles of the carrier phase through an ambiguity fixing algorithm; Iterating the initial baseline vector based on the integer cycle number and the carrier phase to obtain a baseline vector; The relative position information is determined based on the baseline vector, the first positioning data, and the second positioning data.

3. The method according to claim 1, wherein After the step of calculating the relative position information between the golf bag car and the remote controller based on the first positioning data and the second positioning data using a differential correction algorithm, the method further includes: When an interruption of the first positioning data and / or the second positioning data is detected, acquiring corresponding inertial sensor data; performing dead reckoning based on the inertial sensor data to generate displacement compensation data; The displacement compensation data is integrated into the calculation result of the differential correction algorithm to update the relative position information.

4. The method according to claim 1, wherein The step of moving according to the response path to respond to the summon request includes: Obtaining a cost map and determining a cost value for a grid in the cost map; Determining a safe area in the course map according to the cost value; The response path is locally adjusted according to the safety area, and movement is performed according to the adjusted response path.

5. The method according to claim 4, wherein Before the steps of obtaining a cost map and determining the cost value of a grid in the cost map, the method further includes: Retrieving the course map, and obtaining static obstacle information and area information from the map semantic information of the course map; rasterizing the course map to obtain a rasterized map; The cost value is assigned to a grid in the rasterized map according to the static obstacle information and the region information to obtain the cost map.

6. The method according to claim 4, wherein Before the step of locally adjusting the response path according to the security area and moving according to the adjusted response path, the method further includes: Collect the environmental image of the golf cart through the camera; Segmenting the environment image using a semantic segmentation model to identify image feature information; Comparing the image feature information with the course map, and correcting the map deviation according to the comparison result; The safety area is updated based on the correction result of the map deviation.

7. The method according to claim 1, wherein After the step of moving according to the response path to respond to the call request, the method further includes: Determining the relative distance of the remote controller based on the real-time relative position information; When the relative distance is less than a preset distance, identifying the target point in the environment image captured by the camera through a semantic segmentation model; Determine a target point position corresponding to the target point; The docking position is adjusted according to the target point position, and the vehicle is moved to the docking position.

8. The method according to claim 1, wherein After the step of moving according to the response path to respond to the call request, the method further includes: In the stadium map, determining the boundaries of the penalty area; When the distance between the first positioning data and the restricted area boundary is less than a safety distance threshold, triggering emergency braking; An action of replanning the response path is executed.

9. A positioning-based remote control response device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the positioning-based remote control response method according to any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the positioning-based remote control response method according to any one of claims 1 to 8 are implemented.

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