An automated system for simulating professional athlete interactions using advanced technology

Abstract

The present invention relates to an automated system (100) for simulating professional athlete interactions using advanced technology. The system (100) comprises a data capturing module, an analyzing module, a personality analysis module, a decision management module, a robotic arm / robot module, drone enrichment module, a governance module and a feedback loop. The data capturing module is configured to gather athlete information from plurality of sources. The analyzing module is configured for analyzing athlete performance metrics. The decision management module configured to generate optimized decisions. The real-time dynamic command generation module generates real- time commands based on analyzed data from plurality of analysis modules. The robotic arm / robot module receives the commands and executes physical actions based on the instructions received. The drone enrichment module enhances situational awareness through strategic aerial data capture. The feedback loop ensures continuous refinement of analysis processes and command generation algorithms through real-time feedback.

Description

DESCRIPTION N AUTOMATED SYSTEM FOR SIMULATING PROFESSIONAL ATHLETE INTERACTIONS USING ADVANCED TECHNOLOGYTechnical Field

[0001] The present invention relates to a field of sports technology and robotics, and more particularly to an automated system for simulating professional athlete interactions using advanced technology.Background Art

[0002] The field of sports analysis has seen significant advancements in recent years, particularly in the realm of computer algorithms and database structures. These technologies have been instrumental in enhancing our understanding of player performance and skill development across various sports disciplines. In the context of cricket, for instance, these technologies have been used to track player movements and playing techniques, providing valuable feedback and insights that can help improve player performance. Though these technologies provide real-time feedback, there are no mechanisms to actually mimic a player whose actions have been recorded and can be used to deliver the same results through a mechanical machine using Al technologies, especially generative Al and quantum computing, and robotics or human-powered devices. Automatic pitching machines or similar devices, such as slingshots, can mimic the action. Replicating the intricate skills and movements of professional athletes has significant applications in training and entertainment. Traditional approaches face limitations in mobility, cost, and complexity. Therefore, there remains a need in the art for an automated system for simulating professional athlete interactions using advanced technology that does not suffer from the above-mentioned deficiencies or at least provides a viable and effective solution.Summary of Invention

[0003] An embodiment of the present invention is to provide an automated system for simulating professional athlete interactions using advanced technology. The system comprises a data capturing module, an analyzing module, a decision management module, a real-time dynamic command generation module, a robotic arm / robot module, drone enrichment module, a governance module and a feedback loop. The data capturing module is configured to gather athlete information from plurality of sources; wherein the plurality of sources comprises plurality of athlete performance metrics derived from video capture, scenerio generation,recordings from professional games, training sessions, utilizing cameras and drones, health reports, manually created data, and injuries / age information, social media and life events, and mental conditions and plurality of sensors to track the movements of the athletes and to capture the motion in three dimensions. The analyzing module is configured for analyzing athlete performance metrics, comprises: a scene analysis module is configured for analyzing video capture and scenario generation; wherein the scene analysis module integrates Al-powered video analysis for enhanced scene interpretation, uses quantum computing for rapid object detection and tracking, applies quantum algorithms for analyzing complex spatial-temporal data relationships, and employs generative models for dynamic real-time event detection; a fitness analysis module analyzes health-related data to assess and forecast players fitness levels; wherein the fitness analysis module incorporates multi-source data aggregation enhanced by quantum computing for fast data integration, incorporates biometric sensors with quantum- enhanced precision for real-time measurements, uses generative Al to analyze historical data for predictive insights, and provides personalized fitness recommendations optimized by quantum algorithms, and a personality analysis module analyzes players personality traits and their impact on performance; where the personality analysis module integrates social and behavioral analytics with generative Al models, enhances psychometric evaluation with quantum computing for complex trait measurement, utilizes generative models for behavioral trend analysis to track personality changes, and employs quantum algorithms for accurate predictive behavior modeling. The decision management module configured to generate optimized decisions based on feedback. The real-time dynamic command generation module generates real-time commands based on analyzed data from plurality of analysis modules; wherein the real-time dynamic command generation module dynamically changes the situation based on voice commands or similar user inputs. The robotic arm / robot module receives the commands and executes physical actions based on the instructions received; wherein the robotic arm / robot module controls and coordinates the actions of ball launchers, articulated arms, drones, humanoid robots, and AR technologies to simulate plurality of athletic maneuvers. The drone enrichment module enhances situational awareness through strategic aerial data capture. The feedback loop ensures continuous refinement of analysis processes and command generation algorithms through real-time feedback. The governance module checks the training is done in a fair and explainable manner and output is explainable and trustworthy. The system that checks if an action produced in a sports activity is not harmful or lethal to other players, such as preventing a delivery that may hit a batsman's head from being bowled or stopping a footballer from kicking another player.

[0004] In accordance with an embodiment of the present invention, the data capturing module also includes different parameters like age group, ground condition, and geographies.

[0005] In accordance with an embodiment of the present invention, the real-time dynamic command generation module utilizes multilingual voice commands.

[0006] In accordance with an embodiment of the present invention, the robotic arm / robot module simulate plurality of athletic maneuvers such as passing, dribbling, shooting, and strategic positioning in sports like football, basketball, tennis, and more, to enhance athletic training scenarios.

[0007] In accordance with an embodiment of the present invention, the feedback loop includes self learning technique.

[0008] In accordance with an embodiment of the present invention, the drone enrichment module includes real-time analysis of environmental factors, opponent positioning, and tactical insights, utilizing Al-driven algorithms for dynamic adjustment of team strategies and player positioning.Technical Problem

[0009] Current sports analysis technologies, while effective in tracking and providing real-time feedback on player performance using computer algorithms, sensor data, and Al, lack the capability to physically replicate the precise movements and skills of professional athletes. Existing mechanical systems like automatic pitching machines or slingshots are limited in adaptability, motion fidelity, and dynamic control, making them unsuitable for accurately mimicking the intricate techniques of individual players. Furthermore, these systems often involve high costs, operational complexity, and restricted functionality. There is, therefore, a technical problem in the absence of an integrated, intelligent, and adaptive system that utilizes advanced technologies such as generative Al, quantum computing, and robotics or human- actuated devices to simulate real athlete interactions in a realistic, responsive, and efficient manner for use in sports training, performance enhancement, and entertainmentSolution to Problem

[0010] To address these limitations, the proposed invention introduces an integrated and intelligent system capable of accurately simulating professional athlete interactions using a combination of generative Al, quantum computing, and robotic or human-actuated mechanisms. Unlike traditional machines limited to repetitive motions, this system leveragesmulti-source data capture and advanced analysis modules to understand and replicate the nuanced biomechanical, psychological, and strategic behaviors of athletes. By incorporating real-time feedback loops, adaptive command generation, and situational awareness through drone-enriched perspectives, the invention ensures responsive, realistic, and personalized simulations. Furthermore, it includes governance protocols to ensure safety, explainability, and ethical training practices. This comprehensive solution provides a significant advancement in the field of sports training, performance enhancement, and interactive entertainment by delivering highly dynamic and intelligent athlete behavior replication.Advantageous Effects of Invention

[0011] An object of the present disclosure is to provide an automated system for simulating professional athlete interactions using advanced technology.

[0012] An object of the present disclosure is to provide a system that can learn from the videos and actions of players in real-time (personas) in different conditions, including but not limited to geography, health conditions, age conditions, stamina level of the player, and weather conditions, among others. An example could be training a bowler like Shane Warne or Kapil Dev.

[0013] An object of the present disclosure is to provide a system that can be tuned to select a particular geography and match situation, and mimic the actual player based on this selection. This selection can be command-based, voice-based, or text-based.

[0014] Still another object of the present disclosure is to provide a system that can be tuned to mimic a particular situation and replicate it in the real world.

[0015] Still another object of the present disclosure is to provide a system that can identify the stamina level and weak areas of the player, and deliver similar bowling scenarios to strengthen the player accordingly

[0016] Yet another object object of the present disclosure is to provide a system through which any player can select a pre-trained player and practice against it in real-time in the physical world.

[0017] Yet another object object of the present disclosure is to provide a system that can change different situations of a match or environment in real-time using voice commands or similar techniques

[0018] Yet another object object of the present disclosure is to provide a system that can learn from the opposite player’s learning curve and suggest personalized training methods and techniques through customized training programs.

[0019] Yet another object object of the present disclosure is to provide a system through which individuals can train by interacting with the system (e.g., a robot) or a simple user interface featuring training videos and actions of players. The system can then mimic these actions and replicate them accurately.

[0020] Yet another object object of the present disclosure is to provide a system that can capture and mimic actual circumstances. For example, a bowler like Kapil Dev would bowl differently on a sunny day compared to a rainy day. Additionally, the system would be trained on different datasets, such as the bowling actions of the same player across different age groups, to accurately replicate these variationsBrief Description of Drawings

[0021] Fig 1: illustrate a block diagram of an automated system for simulating professional athlete interactions using advanced technology, in accordance with an embodiment of the present invention

[0022] Fig 2: illustrate a workflow of decision management module of an automated system for simulating professional athlete interactions using advanced technology, in accordance with an embodiment of the present invention.Description of Embodiments

[0023] Fig 1 : illustrate a block diagram of an automated system for simulating professional athlete interactions using advanced technology, in accordance with an embodiment of the present invention. The system (100) comprises a data capturing module, an analyzing module, a decision management module, a real-time dynamic command generation module, a robotic arm / robot module, drone enrichment module and a feedback loop. The data capturing module is configured to gather athlete information from plurality of sources; wherein the plurality of sources comprises plurality of athlete performance metrics derived from video capture, scenerio generation, recordings from professional games, training sessions, utilizing cameras and drones, health reports, manually created data, and injuries / age information, social media and life events, and mental conditions and plurality of sensors to track the movements of the athletes and to capture the motion in three dimensions. The analyzing module is configured for analyzing athlete performance metrics, comprises: a scene analysis module is configured foranalyzing video capture and scenario generation; wherein the scene analysis module integrates Al-powered video analysis for enhanced scene interpretation, uses quantum computing for rapid object detection and tracking, applies quantum algorithms for analyzing complex spatial- temporal data relationships, and employs generative models for dynamic real-time event detection; a fitness analysis module analyzes health-related data to assess and forecast players fitness levels; wherein the fitness analysis module incorporates multi-source data aggregation enhanced by quantum computing for fast data integration, incorporates biometric sensors with quantum-enhanced precision for real-time measurements, uses generative Al to analyze historical data for predictive insights, and provides personalized fitness recommendations optimized by quantum algorithms and a personality analysis module analyzes players personality traits and their impact on performance; where the personality analysis module integrates social and behavioral analytics with generative Al models, enhances psychometric evaluation with quantum computing for complex trait measurement, utilizes generative models for behavioral trend analysis to track personality changes, and employs quantum algorithms for accurate predictive behavior modeling. The decision management module configured to generate optimized decisions based on feedback. The real-time dynamic command generation module generates real-time commands based on analyzed data from plurality of analysis modules; wherein the real-time dynamic command generation module dynamically changes the situation based on voice commands or similar user inputs. The robotic arm / robot module receives the commands and executes physical actions based on the instructions received; wherein the robotic arm / robot module controls and coordinates the actions of ball launchers, articulated arms, drones, humanoid robots, and AR technologies to simulate plurality of athletic maneuvers. The drone enrichment module enhances situational awareness through strategic aerial data capture. The feedback loop ensures continuous refinement of analysis processes and command generation algorithms through real-time feedback. The governance module checks the training is done in a fair and explainable manner and output is explainable and trustworthy. The system that checks if an action produced in a sports activity is not harmful or lethal to other players, such as preventing a delivery that may hit a batsman's head from being bowled or stopping a footballer from kicking another player.

[0024] In accordance with an embodiment of the present invention, the automated system (100) integrates advanced technologies to simulate professional athlete interactions across various sports. The system (100) comprises:

[0025] High-precision ball launchers and kickers: These components are programmable to simulate kicks, throws, serves, and shots with variable speed, angle, and spin, enhancing the realism of athletic maneuvers.

[0026] Articulated robotic arms: The robotic arms mounted on mobile platforms, are equipped with multiple degrees of freedom enabling them to perform complex athletic maneuvers such as dribbling, serving, and tactical movements.

[0027] Aerial drones: The drones are equipped with cameras and motion control systems, drones provide dynamic movement and equipment delivery, offering overhead perspectives and enhancing situational awareness during simulations.

[0028] Advanced humanoid robots: The humanoid robots are programmed with specific athletic skills and behaviors, humanoid robots replicate the physical presence and movements of professional athletes, contributing to realistic interaction scenarios.

[0029] Augmented reality (AR) components: AR glasses or projection mapping systems overlay virtual models of professional athletes onto physical training areas, allowing users to visualize and interact with their movements in real-time.

[0030] Generative Al models: These models simulate complex strategies and adaptive responses based on extensive datasets of professional athlete behaviors, enhancing the realism and effectiveness of training simulations.

[0031] Quantum computing: Quantum computing is utilized within the system (100) to significantly enhance real-time data processing and decision-making, and also quantum computing optimizes performance by rapidly analyzing and responding to dynamic simulation inputs.

[0032] Central control and coordination system: The central control and coordination utilizes machine learning algorithms to replicate the playing styles of professional athletes, integrating data from video analysis, motion capture, and Al models to program the actions of system components accurately.

[0033] In accordance with an embodiment of the present invention, the system (100) initiates by capturing athlete information from plurality of sources including video capture, scenario generation, recordings from professional games, training sessions, cameras, drones, health reports, manually created data, social media, life events, and mental conditions. This data is processed through specialized modules:

[0034] Data capturing module: The system (100) includes a data capturing module designed to gather athlete information from a variety of sources. These sources encompass athlete performance metrics derived from video capture, scenario generation, recordings from professional games and training sessions, data collected via cameras and drones, health reports, manually created data inputs, as well as information on injuries, age, social media activity, life events, and mental conditions. The module utilizes a plurality of sensors to track athlete movements and captures motion in three dimensions.

[0035] Analyzing module: An analyzing module processes athlete performance metrics through several specialized components:

[0036] Scene analysis module integrates Al-powered video analysis for enhanced scene interpretation, utilizes quantum computing for rapid object detection and tracking, applies quantum algorithms for analyzing complex spatial-temporal data relationships, and employs generative models for dynamic real-time event detection.

[0037] Fitness analysis module analyzes health-related data to assess and forecast players' fitness levels, incorporates multi-source data aggregation enhanced by quantum computing for fast data integration, utilizes biometric sensors with quantum -enhanced precision for real-time measurements, employs generative Al to analyze historical data for predictive insights, and provides personalized fitness recommendations optimized by quantum algorithms.

[0038] Personality analysis module analyzes players personality traits and their impact on performance, integrates social and behavioral analytics with generative Al models, enhances psychometric evaluation with quantum computing for complex trait measurement, utilizes generative models for behavioral trend analysis to track personality changes, and employs quantum algorithms for accurate predictive behavior modeling.

[0039] Decision management module configured to generate optimized decisions based on feedback received from the analyzing modules. The module uses Gen Al techniques which can be trained on normal or quantum computers that analyses actions of the players in real time. A highly trained model on a particular persona that analyses players mental and physical levels.

[0040] Real-time dynamic command generation module generates commands in response to analyzed data from the various analysis modules. It dynamically changes the simulation scenario based on voice commands or similar user inputs.

[0041] Robotic arm / Robot module receives commands from the real-time dynamic command generation module and executes physical actions. It controls and coordinates the actions of balllaunchers, articulated arms, drones, humanoid robots, and AR technologies to simulate a variety of athletic maneuvers. The module actually mimics the player based on a particular scenario, health and mental conditions or replicates a scenario.

[0042] Drone enrichment module enhances situational awareness through aerial data capture, providing dynamic perspectives and additional data for analysis and simulation.

[0043] Feedback loop ensures continuous refinement of analysis processes and command generation algorithms through real-time feedback from simulated interactions. The system (100) can be used to train a particular persona through videos or images and learns from the feedback which can be trained. This includes self learning as well.

[0044] Fig 2: illustrate a workflow (101) of decision management module of an automated system for simulating professional athlete interactions using advanced technology, in accordance with an embodiment of the present invention. The decision management module is a critical component designed for ensuring safety in sports by preventing harmful or lethal actions. The module operates through the following steps:

[0045] Receive and validate inputs: The module receives a variety of inputs related to player actions from sensors, cameras, and other monitoring devices. These inputs are validated for accuracy and relevance, ensuring that only reliable data is used for further processing.

[0046] Evaluate action safety: The validated inputs are analyzed to determine whether the action poses a risk of harm or lethality to other players. This evaluation is based on predefined criteria and thresholds that identify potentially dangerous actions, such as a cricket delivery aimed at a batsman's head or a footballer kicking another player.

[0047] Decision point: The module determines if the action is harmful or lethal.

[0048] If No: The system proceeds with real-time dynamic command generation to allow the safe execution of the action.

[0049] If Yes: The system engages a feedback loop to prevent the execution of the harmful or lethal action.

[0050] Real-time dynamic command generation: For actions deemed safe, the module generates dynamic commands in real-time to guide players in executing their actions without posing risks to others.

[0051] Feedback loop: For actions deemed harmful or lethal, the module initiates a feedback loop. This loop sends corrective signals or commands to intervene and prevent the execution of the identified harmful action, ensuring player safety.

[0052] In accordance with an embodiment of the present invention, the system (100) operation begins with a detailed analysis of an athlete's playing style using video footage, motion capture data, and generative Al models. This data informs the programming of the ball launchers, robotic arms, drones, and humanoid robots. During operation, the ball launchers and kickers simulate passes, throws, and shots, while the robotic arms perform dribbling, serving, and tactical movements. Drones provide dynamic interaction and positioning in the training area, and humanoid robots replicate the presence and movements of the athlete. AR glasses or projection systems display the virtual avatar of the athlete, allowing users to see and respond to their movements as if training with them. Quantum computing enhances the system (100) ability to process data and make real-time decisions, improving the accuracy and efficiency of the simulations.

[0053] In accordance with an embodiment of the present invention, the system (100) integrates advanced technologies to support athletes across various applications. In training, it provides a realistic environment where athletes can enhance their skills through simulated interactions with professional athletes, utilizing real-time data analysis and simulation techniques to optimize training effectiveness and provide precise feedback. For entertainment purposes, the system (100) offers fans and enthusiasts an immersive experience by enabling interactions with virtual or robotic professional athletes in real-time, employing augmented reality (AR) and advanced motion capture to create lifelike engagements and personalized experiences. In rehabilitation, the system (100) assists injured athletes in maintaining and recovering their skills and fitness levels within a controlled environment, using tailored rehabilitation programs based on real-time performance data and adaptive training protocols to facilitate safe and effective recovery processes.

[0054] In accordance with an embodiment of the present invention, the system (100) learns for a specific persona based on different dynamic situations like age group, ground condition, geographies using Gen Al or Gen Al on quantum and robotics or similar techniques and them mimics a particular situation of the persona. The system (100) also anaylzes fitness level, health conditions of the persona by using Al techniques. The system (100) can then change the situation dynamically based on voice commands or similar of the user needs.

[0055] In accordance with an embodiment of the present invention, the system (100) integrates multiple technologies to replicate the actions of professional athletes in various sports. It includes advanced ball launchers and kickers, articulated robotic arms, drones for dynamic movement, humanoid robots, AR for visual representation, generative Al for realistic behavior simulation, and quantum computing for enhanced processing capabilities. The system (100) is designed to simulate various athletic maneuvers such as passing, dribbling, shooting, and strategic positioning in sports like football, basketball, tennis, and more.

[0056] In accordance with an embodiment of the present invention, the system (100) offers a novel approach to simulating professional athlete interactions, providing a versatile and realistic training tool. By combining ball launchers, robotic arms, drones, humanoid robots, augmented reality, generative Al, and quantum computing, the system (100) overcomes the limitations of traditional methods and opens new possibilities in sports training and entertainment

Claims

ClaimsWhat is claimed is:

1. An automated system (100) for simulating professional athlete interactions using advanced technology, comprising: a data capturing module is configured to gather athlete information from plurality of sources; wherein the plurality of sources comprises plurality of athlete performance metrics derived from video capture, scenerio generation, recordings from professional games, training sessions, utilizing cameras and drones, health reports, manually created data, and injuries / age information, social media and life events, and mental conditions and plurality of sensors to track the movements of the athletes and to capture the motion in three dimensions; an analyzing module is configured for analyzing athlete performance metrics, comprises: a scene analysis module is configured for analyzing video capture and scenario generation; wherein the scene analysis module integrates Al-powered video analysis for enhanced scene interpretation, uses quantum computing for rapid object detection and tracking, applies quantum algorithms for analyzing complex spatial -temporal data relationships, and employs generative models for dynamic real-time event detection; a fitness analysis module analyzes health-related data to assess and forecast players fitness levels; wherein the fitness analysis module incorporates multi-source data aggregation enhanced by quantum computing for fast data integration, incorporates biometric sensors with quantum-enhanced precision for real-time measurements, uses generative Al to analyze historical data for predictive insights, and provides personalized fitness recommendations optimized by quantum algorithms; a personality analysis module analyzes personality traits and performance impact of players;where the personality analysis module integrates social and behavioral analytics with generative Al models, enhances psychometric evaluation with quantum computing for complex trait measurement, utilizes generative models for behavioral trend analysis to track personality changes, and employs quantum algorithms for accurate predictive behavior modeling; a decision management module configured to generate optimized decisions based on feedback; a system that checks if an action produced in a sports activity is not harmful or lethal to other players, such as preventing a delivery that may hit a batsman's head from being bowled or stopping a footballer from kicking another player; a governance module checks the training is done in a fair and explainable manner and output is explainable and trustworthy; a real-time dynamic command generation module generates real-time commands based on analyzed data;Wherein the real-time dynamic command generation module dynamically changes the situation based on voice commands or similar user inputs; a robotic arm / robot module is operationally connected with real-time dynamic command generation module, configured to receive the commands and executes physical actions based on the ouput; wherein the robotic arm / robot module controls and coordinates the actions of ball launchers, articulated arms, drones, humanoid robots, and AR technologies to simulate plurality of athletic maneuvers; a drone enrichment module is configured to improve understanding through aerial data capture; feedback loop ensures continuous refinement of analysis processes and command generation algorithms through real-time feedback.

2. The system (100) as claimed in claim 1, wherein the data capturing module includes other different parameters like age group, ground condition, geographies.

3. The system (100) as claimed in claim 1, wherein the real-time dynamic command generation module utilizes multilingual voice commands.

4. The system (100) as claimed in claim 1, wherein the robotic ann / robot module simulate plurality of athletic maneuvers such as passing, dribbling, shooting, and strategic positioning in sports like football, basketball, tennis, and more, to enhance athletic training scenarios.

5. The system (100) as claimed in claim 1, wherein the feedback loop includes self learning technique.

6. The system (100) as claimed in claim 1, wherein the drone enrichment module includes realtime analysis of environmental factors, opponent positioning, and tactical insights, utilizing Al-driven algorithms for dynamic adjustment of team strategies and player positioning.

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