638 results about "Tennis ball" patented technology

The present disclosure discloses a tennis ball-picking robot, including a chassis assembly, a ball-entering control element group, and a ball-collecting mechanism, the ball-entering control element group being disposed on a front end of the chassis assembly and the ball-collecting mechanism being disposed on a rear side of the chassis assembly. The tennis ball-picking robot incorporates multiple AI technologies such as computer vision, simultaneous localization and mapping, and robotics kinematics, enabling intelligent following, mapping and localization, and path planning. The robot can efficiently collect the tennis balls dropped on the court, and the players can also select a ball-picking area and a ball-picking speed pattern of the robot through an APP, improving the ball-picking efficiency, avoiding consuming the physical power of the players due to manual picking, improving the training effect by ultimately ensuring their focus during training, and reducing the training cost.

The invention provides a tennis ball serving robot and a tennis ball serving system, the tennis ball serving robot responds to a user-defined ball serving instruction of a user, enters a user-defined ball serving mode based on the user-defined ball serving instruction of the user, and performs user-defined ball serving according to received user-defined ball serving parameters in the user-defined ball serving mode. The consistency and switching control of tennis ball falling points can be improved, and the ball serving route is improved; the interaction is more visual and simpler; the capability and the application scene of the tennis serving robot are improved; and equipment maintenance is safer and more convenient.

The invention provides a tennis machine and a control method thereof.The tennis machine comprises a camera device, a control device, a goal device and a serving device, the tennis machine captures image data of a user in real time through the camera device and transmits the image data to the control device, so that the control device classifies the image data based on indication action information, and sends the classified image data to the control device; and further determining scoring parameters for controlling the scoring device to transmit the tennis balls and serving parameters for controlling the serving device to serve the tennis balls according to the image data. According to the scheme provided by the invention, the image data of the user can be captured in real time through the camera device, the action of the user can be accurately judged, and the goal parameter and the serving parameter are intelligently determined by the control device according to different image data, so that intelligent adjustment is performed based on the real-time demand of the user; the interactivity and personalization of training by using the tennis machine are improved, the training efficiency and quality can be effectively improved, and the training effect and the use experience of the user are greatly optimized.

The invention relates to the technical field of sports match analysis, and discloses a tennis real-time AI evaluation system based on multi-view visual feature fusion, which comprises the steps of acquiring multi-angle video stream data of a tennis match, fusing multi-view data by using a time sequence diagram convolutional network to generate spatial-temporal feature representation, and constructing a time sequence cause and effect diagram model based on the fused spatial-temporal features. Key turning points of a match are identified by utilizing graph structure analysis and event influence evaluation, the influence of the turning points is verified through an anti-factual reasoning technology, and personalized tactical suggestions are generated in combination with a player feature model. According to the method, mining and understanding of a deep causal mechanism of the competition are realized by constructing the time sequence causal graph model and identifying the key turning points, and more accurate technical and tactical analysis and decision support are provided for coaches and players.

An adhesive for a tennis ball includes base rubber. The base rubber contains, as a main component thereof, liquid rubber having a number average molecular weight of not less than 10,000. The adhesive has a shear viscosity of not greater than 2,000 Pa·s. A tennis ball includes a hollow core made of a rubber material. The core includes two hemispherical half cores. The two half cores are adhered to each other by using the adhesive for a tennis ball.

Provided is a system for robotic collaboration. A first robotic device executes a first action and a second robotic device executes a second action upon the first robotic device completing the first action. An application of a communication device is paired with the first robotic device and the second robotic device. The application is configured to receive at least one input designating, for example, a hitting speed of a tennis ball, a hitting direction of a tennis ball, a unique tag of a subarea in a map of an environment, a task schedule of the first robotic or second robotic device, a driving speed, a selection of a particular user profile, an instruction to drive to a user-identified location, an instruction to turn in a left or right direction, an instruction to drive forwards or backwards, an instruction to stop moving, etc.

A method, apparatus, and system are disclosed for a robot with tennis ball gathering capabilities. A robot is configured to collect, transport, and deposit for storage tennis balls and other light-mobile sports equipment such as are used in table tennis, badminton, squash, pickleball, golf, basketball, dodgeball, floor hockey, indoor soccer, etc., to assist a player in practice without need for additional support personnel or manual ball retrieval by the player.

The embodiment of the invention discloses a real-time tennis ball speed calculation method and system based on a sliding window, and the method comprises the steps: carrying out the data buffering through employing a 35-frame first-in first-out buffer region based on a three-dimensional track point, screening effective points, calculating the instantaneous speed according to a Euclidean distance formula and an inter-frame time interval, and obtaining the real-time tennis ball speed. And through a three-frame sliding window average smooth speed curve, abnormal values are filtered by using a 10-220km / h threshold value, and ball speed calculation is realized. Through three-dimensional track points, ball speed calculation is realized through the steps of data buffering, effective point screening, instantaneous speed calculation, sliding window averaging, threshold filtering and the like. Compared with traditional single-point speed measurement, the precision is improved by about 20% by means of three-frame sliding window and three-dimensional coordinate calculation, and single-frame errors are reduced; the robustness in a complex scene is enhanced through data screening, window averaging and threshold filtering; the process is simple, the calculated amount is small, and the real-time requirement of occupational competitions is met; a fixed 35-frame buffer area optimizes resources, and memory redundancy is avoided.

The embodiment of the invention discloses a three-dimensional tennis track real-time reconstruction method and system based on multiple cameras, internal and external parameters and calibration results of the multiple cameras are utilized, respective two-dimensional pixel coordinates are converted into three-dimensional rays, and nodes are positioned in combination with a minimum distance algorithm. According to the embodiment of the invention, the real-time reconstruction of the three-dimensional track of the tennis ball is realized by virtue of the synchronous multi-camera two-dimensional image through the steps of camera accurate calibration, two-dimensional to three-dimensional ray conversion, intersection point calculation and screening, data output and the like. Compared with the prior art, the reconstruction precision is improved through accurate calibration and ray intersection screening; by means of multi-camera data synchronization and simple calculation process, data delay is reduced, and real-time performance is prominent; by means of multi-camera data redundancy and a placeholder mechanism, the robustness in a complex environment is enhanced; the output three-dimensional point data can directly support the functions of ball speed calculation and the like, and the expansibility is good.

An adhesive for a tennis ball of the present disclosure includes base rubber and a filler. The base rubber contains, as a main component thereof, liquid rubber having a number average molecular weight of not less than 10,000. The filler has an average nitrogen specific surface area of not less than 40 m2 / g. A tennis ball of the present disclosure includes a hollow core made of a rubber material. The core includes two hemispherical half cores. The two half cores are adhered to each other by using the adhesive for a tennis ball.

The invention discloses a tennis racket batting data monitoring system based on an intelligent sensor, and particularly relates to a training data monitoring technology, which comprises a four-layer collaborative architecture, an intelligent tennis racket, an intelligent bracelet and a communication module, the four-layer collaborative architecture is composed of a sensor layer, an unmanned aerial vehicle collaborative layer, an edge computing layer and a cloud / user layer; a first communication module is arranged in the unmanned aerial vehicle cooperation layer and used for receiving racket data and environment perception, and the unmanned aerial vehicle cooperation layer communicates with the sensor layer in real time. According to the tennis racket ball hitting data monitoring system based on the intelligent sensor, comprehensive monitoring and analysis of tennis ball hitting data are achieved, the system can capture detailed information at the ball hitting moment, and an accurate ball hitting quality score is generated in combination with physiological data and environmental factors of players; scientific training feedback and competition strategy support are provided for players; the self-adaptive feedback control function of the system can dynamically adjust the training intensity according to the physical state of the player, and the training effect is effectively improved.

A table tennis recognition system based on YOLOv8 and an edge computing device deployment method belong to the technical field of computer vision, the table tennis recognition system comprises a camera, an edge computing device and a pitching machine, the camera and the pitching machine are connected with the edge computing device, and the edge computing device is connected with a main control center. The table tennis ball recognition system comprises the following steps: S1, image acquisition; s2, image preprocessing; s3, the YOLOv8 network is improved; s4, training a network model; s5, carrying out RKNN conversion on the model, and carrying out quantization processing; and S6, deploying to Orange Pi5Plus (Orange Pi5Plus), and carrying out multi-thread real-time detection on the table tennis ball. According to the system, a training mode instruction is received according to the specific requirement of a user, and the ball serving machine is controlled to serve balls according to a specified mode after the training mode instruction is processed by orange pie 5Plus; a personalized serving strategy can be customized according to the actual training performance of the user, and the coordinate position of the ball is displayed in real time; according to the invention, high-efficiency and low-cost real-time table tennis ball detection and analysis are realized.

The invention relates to the technical field of tennis recognition, in particular to a tennis recognition model based on adaptive illumination variation, which obtains an image brightness histogram by inputting an image, recognizes a region with uneven illumination distribution, and executes local contrast enhancement and global modeling, thereby effectively enhancing details of a target region, and improving the recognition accuracy. And the detectability of the tennis ball under weak light and complex light is improved. In combination with multi-scale feature extraction and classification identification, robust detection of tennis balls in different sizes and motion states is realized, and the method is suitable for multi-angle and light source interference scenes. And meanwhile, trajectory prediction and restoration are performed on detection results in continuous image frames by adopting a DeepSORT algorithm, so that the space-time continuity of target tracking is guaranteed, and target loss caused by detection interruption is avoided. The whole scheme integrates image enhancement, detection and tracking mechanisms, improves the accuracy and stability of tennis recognition under a dynamic illumination condition, and is suitable for a complex tennis outdoor competition environment.

The tennis ball picking machine comprises a base, a ball picking assembly and a driving wheel set assembly used for driving the base to advance are arranged on the base, the ball picking assembly comprises a ball collecting bin fixedly arranged on the base, a ball inlet is formed in the front end of the ball collecting bin, and a shovel plate is arranged at the front end of the bottom of the ball inlet. According to the tennis ball picking machine, the ball collecting bin and the shovel plate are arranged, the rotating roller is arranged above the shovel plate, friction acting force is formed on tennis balls through rotation driving of the roller so that the tennis balls can roll rapidly, the front end of the shovel plate makes contact with the lower portions of the tennis balls, the balls are rolled to the guide plate through the rolling speed, and the balls are picked up through the downward gradient of the guide plate. The tennis balls are collected into the ball collecting bin, the guide plate at the rear end of the ball collecting bin is provided with a corresponding gap reserved with the ball supporting plate, it can be guaranteed that the balls smoothly roll to the ball supporting plate through downward inertia, the phenomenon that the balls are clamped by the ball supporting plate is avoided, and the balls are conveyed to the basket through the bucket type lifting mechanism.

The tennis ball launching device comprises a vehicle body, a transportation assembly and a launching assembly, the vehicle body is provided with a temporary storage bin, the temporary storage bin is used for storing tennis balls, the transportation assembly is arranged on the vehicle body, one end of the transportation assembly is communicated with the temporary storage bin, and therefore the tennis balls in the temporary storage bin can be transported through the transportation assembly; the launching assembly comprises a launching tube, a first launching part and a second launching part, the launching tube is arranged on the transportation assembly and communicates with the transportation assembly, and the launching tube can rotate around the width direction of the vehicle body relative to the vehicle body so as to adjust the launching angle of the launching tube; the first launching part and the second launching part are both arranged on the launching tube, at least parts of the first launching part and the second launching part are located in the launching tube, the first launching part is used for positioning a tennis ball, the second launching part is located on the side, away from the conveying assembly, of the first launching part, and the second launching part is used for accelerating the tennis ball. The tennis ball launching device has the advantages of being simple in structure, high in hit rate and the like.

The invention discloses a sensing and planning method for automatic ball picking of a tennis ball picking robot. The sensing and planning method mainly comprises the four parts of visual sensing, map state updating, path planning and robot motion planning. According to the method, based on a camera carried by a ball picking robot, computer vision and artificial intelligence technologies are utilized to perceive, recognize and position tennis coordinates in a local visual field; according to the method, time-space fusion and task planning are carried out in combination with historical local view perception information, global scanning mapping in advance or sensors depending on global positioning are not needed, the ball picking efficiency is improved on the premise that more sensors are not used, and a ball picking area is not missed.

A tennis ball serving robot and a tennis ball serving system. The tennis ball serving robot comprises a robot body (1), a ball collection basket (10), a controller (11), a ball feeding module (12), a ball launching module (13) and a direction module, wherein the controller (11) is configured to enter a customized ball serving mode in response to a customized ball serving instruction of a user; in the customized ball serving mode, the controller (11) controls, on the basis of received customized ball serving parameters, the ball feeding module (12), the ball launching module (13) and the direction module to work cooperatively, so as to realize the customized ball serving of tennis balls.

The invention discloses a ball core size detection device for tennis ball production, and relates to the technical field of sporting goods manufacturing, the ball core size detection device comprises a conveying mechanism, and the conveying mechanism comprises a conveying frame, a first conveying belt, a second conveying belt and a conveying motor. The contact type measuring probe is in contact with the surface of the ball core, corresponding thickness parameters are measured, relevant size parameters of the ball core are accurately measured, the ball core is shot and imaged through the visual camera, the ball core is annularly scanned in multiple directions through the laser scanning sensor, and position data of all points on the surface of the ball core can be collected. Through the synergistic effect of the contact type measuring probe, the visual camera and the laser scanning sensor, various size parameters of the tennis ball core can be comprehensively and accurately obtained, the detection precision is greatly improved, errors possibly caused by a single measuring mode are effectively reduced, accurate control over the size of the ball core is ensured, and the detection accuracy is improved. And the overall quality of the tennis ball core is guaranteed.

The utility model provides a tennis machine which comprises a tennis machine body, a goal module arranged on the upper side of the tennis machine body, a serving module arranged on the inner side of the tennis machine body, a camera shooting module and a processor, and the processor is in signal connection with the camera shooting module and is in driving connection with the goal module and the serving module. The first driving instruction is used for driving the goal module to execute the goal action, and the second driving instruction is used for driving the serving module to execute the serving action. According to the tennis machine, the processor is combined with the camera shooting module, instructions can be dynamically generated according to real-time image data, the requirement for manual operation is reduced, then the goal module and the serving module are accurately driven, the tennis machine can automatically adjust parameters such as the timing, the position and the angle of serving, and the service efficiency is improved. Automatic control of the tennis machine is achieved, and intelligence and interactivity of tennis training are greatly improved.

An intelligent tennis ball collecting system relates to the technical field of tennis court construction and comprises a ball sweeping device and a collecting device, the ball sweeping device comprises a first power mechanism and a ball sweeping rod, and the first power mechanism is used for being installed on a tennis court and is in transmission connection with the ball sweeping rod; the first power mechanism is used for driving the ball sweeping rod to slide in a first preset direction, so that a tennis ball on the tennis court is pushed to a preset area by the ball sweeping rod; the collecting device comprises a second power mechanism and a collecting vehicle, the second power mechanism is used for being installed on the tennis court, the second power mechanism is in transmission connection with the collecting vehicle, and the second power mechanism is used for driving the collecting vehicle to slide in the preset area in the second preset direction so that the collecting vehicle can automatically collect the tennis balls; the first preset direction is perpendicular to the second preset direction. Tennis balls can be collected in a preset area firstly, then the collecting device moves in the preset area to automatically collect the tennis balls, the area of a repeated movement area is reduced, and the tennis ball collecting efficiency is improved.

The invention relates to the technical field of sports auxiliary equipment, and discloses a table tennis auxiliary training method, a storage medium, a device and terminal equipment, and the method comprises the steps: obtaining table position information through a depth camera, and constructing a three-dimensional coordinate system according to the calibration information of the depth camera and the table position information; acquiring a first table tennis motion image through a depth camera; obtaining table tennis coordinate values based on the three-dimensional coordinate system and the first table tennis motion image; according to the table tennis coordinate values, obtaining table tennis motion trails and drop points; the motion track and the drop point of the table tennis ball are projected to the table tennis table through the projector. The table tennis auxiliary training system integrates intelligence, datamation and informatization, and can capture table tennis motion trails and motion information of athletes at the same time. The motion trail of the table tennis ball can be projected to the table tennis table, and meanwhile the motions of athletes can be scored and guided through projection and an AI model. And the efficiency and quality of table tennis training are effectively improved.

The invention discloses table tennis anti-deformation detection equipment, and particularly relates to the technical field of anti-deformation detection, the table tennis anti-deformation detection equipment comprises a support frame, a miniature push electric cylinder, a detection pressure sensor and a multi-point synchronous extrusion detection mechanism; the multi-point synchronous extrusion detection mechanism comprises a sleeving sliding strip, a groove ring, a plurality of hinge blocks, a connecting shaft, a sleeving push rod, a push shaft, a connecting block and a sleeving block; meanwhile, the table tennis anti-deformation detection equipment further comprises a linkage extrusion assembly, a positioning twisting mechanism and an extrusion linkage mechanism. Through the multi-point-position synchronous extrusion detection mechanism and the linkage extrusion assembly, covering type compression resistance detection on multiple point positions of the outer wall of the table tennis ball is achieved, the accuracy of compression resistance detection of the table tennis ball is greatly improved, and therefore the problems that large-area covering detection on the multiple point positions of the outer wall of the table tennis ball is difficult to achieve due to single-direction detection, and the detection accuracy is poor are solved. Therefore, the detection accuracy of the table tennis ball is poor.

The invention discloses an intelligent table tennis ball transmitter, which relates to the technical field of table tennis balls and comprises a video image processing module, a video image recognition module, a training model, a transmitting parameter management system, an image acquisition module, a table tennis ball falling point and track recognition module and a transmitting device. According to the table tennis ball launching machine, launching and rotation of a ball are controlled through the airflow technology, different table tennis ball running paths and falling points are simulated, and targeted training of athletes can be achieved by simulating ball serving of opponents through competition videos and analysis.

The invention discloses a rubber particle preparation method based on recycled tennis balls, an environment-friendly runway construction method and an environment-friendly runway, and belongs to the field of runway construction.The method comprises the following steps that Sa1, the recycled tennis balls with impurities removed are put into a smashing machine at a constant speed, and surface felt and a rubber inner core are smashed and separated through the smashing machine; sa2, disinfection and washing are carried out; sa3, separating the fibers from the rubber particles; sa4, naturally air-drying the fibers and the rubber particles; sa5, classifying and screening; and Sa6, classifying, sealing and storing. By the adoption of the rubber particle preparation method based on the recycled tennis balls, the environment-friendly runway construction method and the environment-friendly runway, vulcanized rubber resources in the waste tennis balls can be efficiently recycled, meanwhile, high-valued application of the resources is achieved through the following environment-friendly runway construction steps, and a complete technical closed loop of recycling, preparation and application is formed.

The invention discloses a deep learning-based tennis ball detection method applied to a video stream. The method comprises the following steps: S10, a data preprocessing stage: performing data preprocessing on a time sequence video stream to obtain training data; s20, a model training stage: stacking a continuous picture sequence and a background frame image in the training data pair through a stacking module to form network training input, performing multi-layer down-sampling through an encoder structure to obtain a feature vector fused with time sequence information, performing processing through a time attention module to improve the enhancement of a small target object, and performing model training; restoring a corresponding thermodynamic diagram of the input time sequence through a decoder structure; through comparison with a thermodynamic diagram of a real label, a loss value is obtained in a weighted loss calculation module, so that model parameters are solved through back propagation; and S30, a model reasoning stage, wherein after network training is completed, video streams are input into the network for reasoning operation to detect the position of the tennis ball.

The utility model discloses a tennis ball serving device, which relates to the technical field of physical training equipment and comprises a base, a rotating mechanism mounted in the base, a rotating disc rotatably connected to the upper end of the base, fixing frames symmetrically connected to the upper end of the rotating disc in a threaded manner, a ball serving device body rotatably connected to the opposite ends of the fixing frames, and a mounting plate connected to the upper end of the rotating disc in a threaded manner. An electric telescopic rod is mounted at the upper end of the mounting plate, an adjusting mechanism is fixedly connected to the telescopic end of the electric telescopic rod, an operating mechanism is mounted at the upper end of the base, a launching assembly is mounted at one end of the pitching device body, and a ball outlet pipe is mounted at the end, away from the launching assembly, of the pitching device body. By the adoption of the structure, the direction and the pitching angle of the pitching machine can be automatically adjusted, players can simulate pitching in different directions and angles, training diversity is improved, meanwhile, the direction and the angle of the pitching machine can be rapidly adjusted according to requirements and plans of the players, and training efficiency is improved. And players are helped to obtain more training results within limited time.

The invention provides an intelligent identification method and system for an air juggling action of a table tennis ball based on deep learning. The method comprises the following steps: step 1, collecting real-time video data and attitude sensor data of air juggling through a mobile terminal; 2, constructing a deep learning action recognition model; 3, optimizing the pre-trained YOLO model by adopting a transfer learning strategy; 4, according to the relative position relation between the racket and the table tennis ball, a multi-constraint-condition ball hitting judgment algorithm is designed; and 5, feeding back an identification result in real time through the mobile terminal, wherein the identification result comprises error action correction demonstration, training report generation and quantitative index display. According to the method, the computer vision technology and the recognition algorithm are utilized, real-time recognition and analysis of the air juggling actions of the teenagers at home are achieved through mobile clients such as mobile phone applets, professional training guidance and feedback are provided for the teenagers, the teenagers are helped to standardize the actions, and the training effect is improved.

The invention discloses a self-walking trolley, and particularly relates to a table tennis and tennis ball picking and serving self-walking trolley which comprises a trolley body forming a storage cavity, a ball picking device is arranged on the trolley body and comprises a first baffle forming a V-shaped groove and a rolling brush motor assembly, and a notch coinciding with a first opening of the storage cavity is formed in the bottom of the V-shaped groove. The rolling brush motor assembly stirs the balls in the V-shaped groove area to move towards the notch of the V-shaped groove, an air channel is formed in the vehicle body and communicated with the storage cavity, and an air channel motor is arranged in the air channel and sucks air in the storage cavity to drive the balls in the notch of the V-shaped groove to overcome the blocking acting force of the blocking piece to enter the storage cavity through the first opening. The technical problem of optimal design of the structure of the ball picking and serving self-walking trolley is solved. The ball picking and serving device has the advantages that the ground trafficability is relatively better, the serving angle can be automatically adjusted, and the ball picking and serving device can adapt to balls with different diameters (including table tennis balls, tennis balls and the like) to pick and serve the balls.

The invention provides a table tennis flaw detection system and electronic equipment, which are characterized in that when a side light source is used for illuminating a table tennis ball at the same time, a high-resolution camera is used for collecting original images of the table tennis ball in parallel, a deep learning algorithm is combined for image capture and analysis, and the system preprocesses the images, extracts features and identifies and classifies flaws. Finally, results are output in parallel, automatic detection is achieved, the image contrast is remarkably enhanced and noisy points are reduced through image preprocessing, the detection precision under small flaws and complex backgrounds is improved, meanwhile, an extraction feature layer of the model is improved, flaws in imaging are accurately found out through a target detection algorithm in deep learning, and the detection accuracy is improved. According to the method, the sensitivity to tiny flaws is enhanced, the problem that feature extraction is insufficient when a traditional convolutional layer processes a complex background is solved, inference delay is reduced through non-NMS training, and therefore the detection precision and real-time performance of the whole system are improved.

The invention relates to a high-motion table tennis trajectory tracking method, which comprises the following steps of: performing motion blur correction on an original table tennis competition video, reducing motion blur, and enabling the edge and the texture of a table tennis to be clearer; then super-resolution reconstruction processing is carried out, the pixels of the table tennis balls in the frame images are increased, and the omission ratio is reduced when the improved YOLOv7 network model is adopted to carry out multi-scale small target detection on the frame images after super-resolution reconstruction subsequently; next, an improved DeepSORT algorithm is adopted to track the bounding box video frame sequence detected in the second step to generate continuous two-dimensional coordinates, tracking position errors are reduced, then a three-dimensional track is obtained through monocular depth estimation and table plane constraint reconstruction, the whole process is subjected to assembly line design, error accumulation of traditional staged processing is avoided, and the tracking accuracy is improved. Four difficulties of small targets, motion blur, shielding and complex backgrounds are jointly solved, and the average success rate gt of the whole process is obtained; 90%.