Golf Ball Resting Position Prediction Using Surface and Shot Data
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Solution Overview
Problem
Existing methods for determining the final resting position of a golf ball during tournament play are inadequate, lacking precision and accuracy in predicting bounce and roll behavior due to insufficient consideration of environmental factors and historical data.
Innovation Solution
A system utilizing predictive analytics with a prediction model that incorporates metadata on ball physics, course environment, and historical shot data to predict bounce and roll behavior, employing detailed surface models and environmental sensors to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional mapping and laser tracking methods are used to determine ball position, then the system is simple to operate, but the measurement precision and prediction accuracy are insufficient
Solution Approach 1:
The system segments the prediction process into multiple independent modules: environmental data collection (temperature, humidity, wind), historical shot data analysis, ball physics modeling, and prediction calculation. Each module processes specific parameters separately, then integrates results to achieve high precision without requiring a monolithic complex system.
Solution Approach 2:
The system performs preliminary actions by pre-collecting and storing environmental data, historical shot data, and ball physics parameters before actual ball tracking. Surface models and prediction algorithms are pre-computed and stored, enabling rapid high-precision predictions during actual play without real-time complex calculations.
2Measurement precision
If detailed surface models and environmental sensors are integrated, then the prediction accuracy improves, but the device complexity increases
Solution Approach 1:
The system merges multiple data sources (environmental sensors, historical databases, surface models) into a unified prediction framework. By combining temperature, humidity, wind data with historical shot data and ball physics models, the system achieves comprehensive prediction accuracy while managing complexity through integrated data processing.
Solution Approach 2:
The prediction system serves multiple functions: it analyzes ball bounce, roll behavior, and final resting position using the same integrated model. The universal prediction algorithm handles various shot types and environmental conditions, reducing the need for separate specialized systems for each prediction task.
3Adaptability or versatility
If historical shot data and environmental factors are incorporated, then the adaptability to real-world conditions improves, but the loss of time for data processing increases
Solution Approach 1:
Environmental data, historical shot data, and ball physics parameters are collected, processed, and stored in advance before actual ball tracking begins. Surface models and prediction algorithms are pre-computed, enabling the system to adapt to real-world conditions during play without requiring time-consuming real-time data processing.
Solution Approach 2:
The system uses historical shot data as copies of actual ball behavior under similar environmental conditions. By referencing these pre-recorded data copies, the system adapts to current environmental conditions without needing to compute every parameter from scratch, significantly reducing processing time while maintaining adaptability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides precise predictions of a golf ball's final resting position by integrating detailed surface models, environmental data, and historical shot data, improving prediction accuracy and adaptability to real-world conditions.
Implementation Method 1
The surface model may comprise a three-dimensional coordinate model, which may comprise a digital surface model measured by lidar
Data Source
AI summary
A system for predicting a resting position of a golf ball may use ball tracking sensor data to identify an impact location of the ball. Modeling of ball movement following impact may be performed that incorporates measured ball impact physics, impact coordinates, and material properties of ground or objects to which the impact coordinates correspond and, together with historical shot data corresponding to the impact coordinates or an encompassing zone, bounce and roll behavior and/or final resting position predictions may be generated.