Automatic driving trolley for middle and long distance running training and control method

Abstract

The invention discloses an automatic driving trolley for middle and long distance running training and a control method, and relates to the technical field of physical training auxiliary equipment, the automatic driving trolley comprises a trolley hardware platform and a sensing positioning module arranged on the trolley hardware platform; the decision control module is arranged on the trolley hardware platform; the man-machine interaction module is electrically connected with the trolley hardware platform; the power supply module is arranged on the trolley hardware platform and is used for supplying power; through the accurate automatic driving technology, constant or programmable speed matching guidance is provided for athletes, the psychological burden of the athletes for calculating the speed matching is relieved, the competition scene is simulated, the training quality and efficiency are effectively improved, and finally the athletes are helped to more efficiently improve the athletic performance and obtain better scores in the competition; physical fluctuation of a human speed matching person is overcome, a preset speed matching strategy can be executed with extremely high precision, and it is ensured that a training plan is strictly and stably executed.

Description

Technical Field

[0001] This invention relates to the field of sports training auxiliary equipment technology, specifically to an autonomous driving vehicle and control method for middle and long-distance running training. Background Technology

[0002] In running training and competition, pacemakers (commonly known as "rabbits") are crucial for athletes to scientifically allocate their energy and achieve their target performance. Traditionally, pacemakers are experienced athletes, but this approach has the following limitations: 1. Scarcity of human resources: The number of high-level pacers is limited and their cost is high, making it difficult to meet the daily training needs.

[0003] 2. Insufficient stability: Human pacers' own condition fluctuates, making it difficult to guarantee an absolutely constant speed, especially in the second half of long distances where deviations are prone to occur.

[0004] 3. Poor customizability: It is difficult to accurately execute complex, segmented pacing strategies (such as negative segmented pacing).

[0005] In recent years, electronic pacing devices such as "Wavelight" have emerged, which guide athletes by installing LED light strips along the track and making them flash at a set speed. These systems solve the problem of pacing stability, but their disadvantages include fixed installation, poor flexibility, inability to adapt to segmented speed training, and lack of psychological support from physical accompaniment.

[0006] While some following robots have emerged, most are designed for logistics, warehousing, or ordinary road following scenarios, and are not optimized for the specific environment of an athletic track. A standard athletic track consists of straight sections and curves, and multiple circular tracks. Current technology lacks a solution capable of: 1. Based on high-precision positioning, it automatically adapts to different track numbers (i.e. curves with different curvatures).

[0007] 2. Solve the problem of maintaining a stable linear speed when driving on curves, so as to ensure the accuracy of the lap time timing for the athlete.

[0008] 3. Deeply integrated with athletes' training plans (distance, time, segments), providing highly customizable pacing solutions.

[0009] In summary, there is a significant gap in the existing technology: the lack of a low-cost, miniaturized automatic pacing device specifically designed for standard athletic tracks, capable of autonomous navigation, precise speed control, obstacle avoidance, and flexible adaptation to various training programs. Summary of the Invention

[0010] The purpose of this invention is to provide an autonomous driving vehicle and control method for middle and long-distance running training, so as to solve the problems mentioned in the background art.

[0011] To address the aforementioned technical problems, this invention provides the following technical solution: an autonomous driving vehicle for middle- and long-distance running training, comprising a vehicle hardware platform and: The sensing and positioning module is installed on the vehicle's hardware platform; The decision control module is installed on the vehicle's hardware platform; A human-machine interface module electrically connected to the vehicle hardware platform; A power supply module installed on the vehicle's hardware platform for power supply.

[0012] As a preferred embodiment of the autonomous driving vehicle for middle and long-distance running training according to the present invention, the vehicle hardware platform includes an aluminum alloy frame, on which a servo motor for driving the wheels to rotate and a joint motor for driving the wheels to steer are provided. A reducer is connected between the servo motor and the wheel. An independent suspension system is provided between the aluminum alloy frame and the wheel. Collision protection is provided at both ends of the aluminum alloy frame.

[0013] As a preferred embodiment of the autonomous driving vehicle for middle and long-distance running training according to the present invention, the anti-collision protection is a crash barrier or a bumper.

[0014] As a preferred embodiment of the autonomous driving vehicle for middle and long-distance running training according to the present invention, the perception and positioning module includes RTK-GNSS, lidar, camera and ultrasonic radar.

[0015] As a preferred embodiment of the autonomous driving vehicle for middle and long-distance running training according to the present invention, the decision control module has built-in speed planning algorithm, path planning algorithm, obstacle avoidance algorithm and steering control algorithm.

[0016] As a preferred embodiment of the autonomous driving vehicle for middle and long-distance running training according to the present invention, the human-computer interaction module has a built-in remote control / wireless Wi-Fi / 4 / 5G / mobile APP / WeChat mini-program.

[0017] As a preferred embodiment of the autonomous driving vehicle for middle and long-distance running training according to the present invention, the power module is a high-energy-density lithium battery pack with a reducer.

[0018] A control method for an autonomous vehicle used for middle- and long-distance running training, applied to the autonomous vehicle for middle- and long-distance running training as described in any one of claims 1-5, wherein the control method for the autonomous vehicle for middle- and long-distance running training includes: Step S1: The athlete or coach sets the training goal through the human-computer interaction module and sends the instructions to the vehicle hardware platform; Step S2: Start the vehicle hardware platform, the power module provides power, the perception and positioning module starts working, and determines its precise pose and track number; Step S3: The decision control module calculates the speed curve based on the target; on the straightaway, it drives strictly at the linear speed corresponding to the target pace; before entering the curve, it calculates the linear speed required to maintain the lap time based on the radius of the curve, smoothly transitions and maintains that speed through the curve; Step S4: While driving, the perception and positioning module continuously scans ahead to detect whether there are any obstacles. Step S5: After training ends or is manually stopped midway, the vehicle hardware platform automatically brakes and comes to a stop; a detailed data report of this training is displayed on the human-computer interaction module.

[0019] As a preferred embodiment of the autonomous driving vehicle control method for middle and long-distance running training of the present invention, in step S2, the power module has a built-in power management circuit, which is responsible for voltage conversion, charging management and power monitoring, and uploads the power information to the human-machine interaction module.

[0020] As a preferred embodiment of the autonomous driving vehicle control method for middle and long-distance running training of the present invention, in step S4, if an obstacle is detected within 5 meters ahead, deceleration is triggered; if the obstacle persists and the distance is less than 2 meters, braking is performed to stop the vehicle, and driving is automatically resumed after the obstacle is cleared.

[0021] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: Through precise autonomous driving technology, it provides athletes with constant or programmable pace guidance, reducing the psychological burden of calculating pace, simulating competition scenarios, effectively improving training quality and efficiency, and ultimately helping athletes improve their athletic performance more efficiently and achieve better results in competitions; it overcomes the physical fluctuations of human pacemakers, executing preset pace strategies with extremely high precision, ensuring that training plans are strictly and stably executed; it supports complex multi-segment interval running training (such as interval running and fartlek running), meeting personalized and scientific training needs; it has an active obstacle avoidance function, effectively avoiding collisions with athletes and eliminating potential safety risks from human pacemakers; a single investment can be used repeatedly for a long time, reducing the expensive cost of hiring high-level human pacemakers; it allows athletes to fully focus on their physical fitness and technical movements without being distracted by pace calculations, thereby maximizing training effects; and through the "constant linear velocity in curves" algorithm, it ensures the accuracy of lap time timing, which is one of the innovative points for track and field scenarios. Attached Figure Description

[0022] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a block diagram of an autonomous driving vehicle and control method for middle and long-distance running training according to the present invention patent. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1 The present invention provides a technical solution: an autonomous driving vehicle for middle and long-distance running training, comprising a vehicle hardware platform and: a perception and positioning module disposed on the vehicle hardware platform; a decision control module disposed on the vehicle hardware platform; a human-machine interaction module electrically connected to the vehicle hardware platform; and a power supply module disposed on the vehicle hardware platform for power supply.

[0025] The vehicle hardware platform includes an aluminum alloy frame, which itself has wheels, a steering structure, and electronic braking functionality—all existing technologies and will not be elaborated upon here. The electronic braking function responds to commands from the decision control module, enabling rapid and smooth braking. The vehicle body structure on the aluminum alloy frame is recommended to adopt a miniaturized and lightweight design to reduce inertia and facilitate acceleration and braking. For example, this application uses aluminum alloy, but high-hardness plastics could also be used. The aluminum alloy frame chassis adopts a low center of gravity design to improve stability when cornering. The aluminum alloy frame is equipped with servo motors that drive the wheels and joints that drive the wheels to steer. The servo motor is connected to the wheel by a reducer. The servo motor uses a high-precision DC brushless motor in conjunction with the reducer to provide smooth torque output, ensuring accurate speed control and response speed. The joint motor uses joint clicks to precisely control steering to adapt to the curves of the track. An independent suspension system is provided between the aluminum alloy frame and the wheel. Anti-collision protection is provided at both ends of the aluminum alloy frame. The anti-collision protection is a crash bar or bumper, and warning devices can also be added. It can be equipped with LED light strips or small buzzers to indicate status (such as start, deceleration, low battery). It is a conventional existing device and belongs to existing technology.

[0026] The perception and positioning module includes RTK-GNSS, lidar, camera, and ultrasonic radar. The RTK-GNSS is a real-time dynamic differential (RTK) GPS module that provides centimeter-level positioning accuracy, enabling the vehicle to accurately determine its specific location on which track it is. The lidar is mounted on the top of the aluminum alloy frame and is a 360-degree radar. The ultrasonic radar is mounted around the aluminum alloy frame to detect obstacles on the track in real time (such as other athletes or fallen objects) and transmit the signals to the decision control module.

[0027] The decision control module incorporates speed planning, path planning, obstacle avoidance, and steering control algorithms. The speed planning algorithm receives target parameters (total distance, total time, segmented distance, and time) from the human-computer interaction module and generates an ideal speed-time curve, aiming to complete the entire course at the most uniform speed possible. The path planning algorithm generates a target driving path based on high-precision positioning data and a preset track number (i.e., track radius). Crucially, the cornering speed compensation algorithm ensures accurate lap times for the athlete, maintaining a constant linear velocity (not angular velocity) required for the set lap speed when driving on curves. This means the car calculates the optimal cornering linear velocity required to maintain the lap speed based on different track radii. The obstacle avoidance algorithm, upon receiving obstacle signals from the perception module, issues commands based on preset safety strategies (such as deceleration, stopping, or slightly deviating from the original path while ensuring safety).

[0028] The human-machine interface module includes a built-in remote control / wireless Wi-Fi / 4G / 5G / mobile APP / WeChat mini-program, with the mobile APP serving as the primary control terminal. Users can set driving parameters via the APP: total distance (100-10000 meters), total time / target pace (10-3000 seconds), segmented plan (time for each 100-400 meter segment), and track number (lane 1-8). The APP can send start, stop, and pause commands to the vehicle and display its status in real time (current position, distance traveled, real-time speed, remaining battery power, etc.). A wireless Wi-Fi / 4G / 5G communication module is used for data interaction with the mobile APP. The remote control is equipped with an independent wireless handle for manual remote control of the vehicle, suitable for debugging or special situations.

[0029] The power module is a high-energy-density lithium battery pack with a speed reducer. The high-energy-density lithium battery pack adopts a detachable design for easy replacement. The battery capacity ensures a range of more than 10 kilometers when fully charged to ensure normal driving. It can also be equipped with a power management circuit (PMIC) to be responsible for voltage conversion, charging management and power monitoring, and to upload power information to the main controller. It is a conventional device.

[0030] A control method for an autonomous vehicle used in middle- and long-distance running training includes: Step S1: The athlete or coach sets the training goal through the human-computer interaction module and sends the instructions to the vehicle hardware platform; Step S2: Start the vehicle hardware platform, the power module provides power, the perception and positioning module starts working, and determines its precise pose and track number; Step S3: The decision control module calculates the birth speed curve based on the target; on the straightaway, it drives strictly according to the linear speed corresponding to the target pace; before entering the curve, it calculates the linear speed required to maintain the lap speed based on the radius of the curve, smoothly transitions and maintains that speed through the curve; Step S4: While driving, the perception and positioning module continuously scans ahead to detect whether there are any obstacles ahead; Step S5: After training ends or is manually stopped midway, the vehicle hardware platform automatically brakes and comes to a stop; a detailed data report of this training is displayed on the human-computer interaction module.

[0031] In step S2, the power module has a built-in power management circuit that is responsible for voltage conversion, charging management, power monitoring, and uploading power information to the human-machine interaction module.

[0032] In step S4, if an obstacle is detected within 5 meters ahead, deceleration is triggered; if the obstacle persists and the distance is less than 2 meters, braking is performed to bring the vehicle to a stop, and driving will automatically resume after the obstacle is cleared.

[0033] How it works: First, athletes or coaches set their training goals via a mobile app. For example, a distance of 5000 meters with a target time of 20 minutes, running in lane 3. They can also set a pace of 84 seconds per lap for the first 2000 meters and 80 seconds per lap for the last 3000 meters. Specific paces can be found in the table below. road number Straight distance Inner radius Curve radius Curving distance One lap distance Equipment turning radius (centerline) Equipment bend distance 1 84.39 36.5 36.8 115.6106097 400.0012193 37.11 116.5845034 2 84.39 36.5 37.92 119.1291934 407.0383868 38.33 120.4172464 3 84.39 36.5 39.14 122.9619365 414.7038729 39.55 124.2499894 4 84.39 36.5 40.36 126.7946795 422.369359 40.77 128.0827325 5 84.39 36.5 41.58 130.6274225 430.0348451 41.99 131.9154755 6 84.39 36.5 42.8 134.4601656 437.7003311 43.21 135.7482186 7 84.39 36.5 44.02 138.2929086 445.3658172 44.43 139.5809616 8 84.39 36.5 45.24 142.1256516 453.0313033 45.65 143.4137046 Distance unit: meter, speed unit: meter / second Taking a 400-meter race at a constant pace of 54 seconds as an example, the average speed is 7.4 m / s, the straightaway completion time is 11.39 seconds, and the curve completion time is 15.607 seconds. The average speeds of the cars placed in lanes 1 through 8 are as follows: road number Straight distance Curving distance One lap distance Equipment bend distance Equipment straight-line speed Equipment curve speed Equipment completion time 1 84.39 115.6106097 400.00 116.5845034 7.407407407 7.469806763 54.00 2 84.39 119.1291934 407.04 120.4172464 7.407407407 7.715378422 54.00 3 84.39 122.9619365 414.70 124.2499894 7.407407407 7.960950081 54.00 4 84.39 126.7946795 422.37 128.0827325 7.407407407 8.206521739 54.00 5 84.39 130.6274225 430.03 131.9154755 7.407407407 8.452093398 54.00 6 84.39 134.4601656 437.70 135.7482186 7.407407407 8.697665056 54.00 7 84.39 138.2929086 445.37 139.5809616 7.407407407 8.943236715 54.00 8 84.39 142.1256516 453.03 143.4137046 7.407407407 9.188808374 54.00 (1) The APP sends instructions to the car via Wi-Fi; (2) The trolley starts, and the RTK-GPS and IMU begin to work to determine its precise position and runway number; (3) The decision control module calculates the birth speed curve based on the target. On the straightaway, it drives strictly at the linear speed corresponding to the target pace. Before entering the curve, it calculates the linear speed required to maintain the lap time based on the radius of the third lane, smoothly transitions, and maintains this speed through the curve; (4) While driving, the lidar continuously scans the front. If an obstacle is detected within 5 meters ahead, deceleration is triggered; if the obstacle persists and the distance is less than 2 meters, braking is performed to bring the vehicle to a stop, and driving will automatically resume after the obstacle is cleared. (5) After the training ends or is manually stopped midway, the car will automatically brake and come to a stop, and the APP will display a detailed data report of this training.

[0034] It is important to note that the constructions and arrangements of this application shown in several different exemplary embodiments are merely illustrative. Although only a few embodiments are described in detail in this disclosure, those who consult this disclosure will readily understand that many modifications are possible (e.g., changes in the size, dimensions, structure, shape, and proportions of various elements, as well as parameter values ​​(e.g., temperature, pressure, etc.), mounting arrangements, use of materials, color, orientation, etc.) without substantially departing from the novel teachings and advantages of the subject matter described in this application). For example, an element shown as integrally formed may be composed of multiple parts or elements, the position of elements may be inverted or otherwise altered, and the nature or number or position of discrete elements may be changed or altered. Therefore, all such modifications are intended to be included within the scope of the invention. The order or sequence of any process or method steps may be changed or rearranged according to alternative embodiments. In the claims, any "device plus function" clause is intended to cover the structure described herein that performs the function, and not only structurally equivalent but also equivalent in structure. Other substitutions, modifications, alterations, and omissions may be made in the design, operation, and arrangement of the exemplary embodiments without departing from the scope of the invention. Therefore, the present invention is not limited to the specific embodiments, but extends to various modifications that still fall within the scope of the appended claims.

[0035] Furthermore, in order to provide a concise description of exemplary embodiments, not all features of actual embodiments (i.e., those features that are not relevant to the best mode of carrying out the invention as currently considered, or those features that are not relevant to implementing the invention) may be omitted.

[0036] It should be understood that numerous specific implementation decisions can be made during the development of any practical implementation, such as in any engineering or design project. Such development efforts may be complex and time-consuming, but for those skilled in the art who benefit from this disclosure, the development effort will be a routine work of design, manufacturing, and production without requiring much experimentation.

[0037] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. An autonomous driving vehicle for middle- and long-distance running training, characterized in that, Including the car hardware platform and: The sensing and positioning module is installed on the vehicle's hardware platform; The decision control module is installed on the vehicle's hardware platform; A human-machine interface module electrically connected to the vehicle hardware platform; A power supply module installed on the vehicle's hardware platform for power supply.

2. The autonomous driving vehicle for middle- and long-distance running training according to claim 1, characterized in that: The vehicle hardware platform includes an aluminum alloy frame, on which a servo motor for driving the wheels to rotate and a joint motor for driving the wheels to steer are mounted. A reducer is connected between the servo motor and the wheel. An independent suspension system is provided between the aluminum alloy frame and the wheel. Collision protection is provided at both ends of the aluminum alloy frame.

3. The autonomous driving vehicle for middle- and long-distance running training according to claim 2, characterized in that: The collision protection is a crash barrier or bumper.

4. The autonomous driving vehicle for middle- and long-distance running training according to claim 1, characterized in that: The perception and positioning module includes RTK-GNSS, lidar, camera, and ultrasonic radar.

5. The autonomous driving vehicle for middle- and long-distance running training according to claim 1, characterized in that: The decision control module has built-in speed planning algorithm, path planning algorithm, obstacle avoidance algorithm and steering control algorithm.

6. The autonomous driving vehicle for middle- and long-distance running training according to claim 1, characterized in that: The human-computer interaction module has a built-in remote control / wireless Wi-Fi / 4 / 5G / mobile APP / WeChat mini-program.

7. The autonomous driving vehicle for middle- and long-distance running training according to claim 1, characterized in that: The power module is a high-energy-density lithium battery pack with a speed reducer.

8. A control method for an autonomous driving vehicle for middle- and long-distance running training according to claim 1, characterized in that: The method for controlling an autonomous vehicle used for middle- and long-distance running training, as described in any one of claims 1-7, comprises: Step S1: The athlete or coach sets the training goal through the human-computer interaction module and sends the instructions to the vehicle hardware platform; Step S2: Start the vehicle hardware platform, the power module provides power, the perception and positioning module starts working, and determines its precise pose and track number; Step S3: The decision control module calculates the speed curve based on the target; on the straightaway, it drives strictly at the linear speed corresponding to the target pace; before entering the curve, it calculates the linear speed required to maintain the lap time based on the radius of the track, smoothly transitions and maintains that speed through the curve; Step S4: While driving, the perception and positioning module continuously scans ahead to detect whether there are any obstacles. Step S5: After training ends or is manually stopped midway, the vehicle hardware platform automatically brakes and comes to a stop; a detailed data report of this training is displayed on the human-computer interaction module.

9. The autonomous driving vehicle control method for middle- and long-distance running training according to claim 8, characterized in that: In step S2, the power module has a built-in power management circuit, which is responsible for voltage conversion, charging management and power monitoring, and uploads the power information to the human-machine interaction module.

10. The autonomous driving vehicle control method for middle- and long-distance running training according to claim 8, characterized in that: In step S4, if an obstacle is detected within 5 meters ahead, deceleration is triggered. If the obstacle remains and the distance is less than 2 meters, the vehicle will brake and come to a stop. Once the obstacle is cleared, the vehicle will automatically resume driving.

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