Hybrid Motion Detection Drift Correction in Game Controllers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing motion detection systems in portable data processing apparatus, such as game machines, suffer from integration errors that lead to drift and inaccuracies in position and orientation detection, affecting user experience in applications requiring precise motion control.
Innovation Solution
A hybrid motion detection system that combines hardware motion detection using accelerometers with video image analysis, where the controller adjusts the operation of the hardware motion detector based on differences between the two methods, allowing for validation and correction of motion data to reduce integration errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hardware motion detection using accelerometers is used, then the device can detect motion and provide control inputs, but integration errors cause drift and reduce measurement precision over time
Solution Approach 1:
The system continuously compares motion data from the accelerometer with visual flow data from the camera, detecting discrepancies and correcting drift through feedback mechanisms. The controller monitors the difference between inertial-based estimates and image-based estimates, adjusting the hardware motion detector operation to maintain accuracy over time.
Solution Approach 2:
The camera acts as an intermediary device that provides an alternative measurement method for motion detection. By capturing visual flow information from the environment, the camera serves as a mediator that validates and corrects the accelerometer's integrated position and orientation data, eliminating the need for direct trust in the drift-prone integration process.
2Ease of operation
If integration processes are used to obtain velocity and position from accelerometer data, then motion control functionality is enabled, but errors and noise accumulate causing drift
Solution Approach 1:
The system implements feedback by continuously comparing the results of integration (position and orientation from accelerometer) with direct visual measurements from the camera. When drift is detected through this comparison, the system adjusts the integration process or resets the accumulated values to maintain accuracy while preserving motion control functionality.
Solution Approach 2:
The patent substitutes the purely mechanical/inertial integration process with a hybrid approach that incorporates optical measurement. Instead of relying solely on mechanical accelerometer integration, the system replaces the position and orientation measurement mechanism with visual flow analysis from the camera, eliminating the accumulation of integration errors.
3Measurement precision
If a video camera and image analysis are added to correct drift, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The camera serves multiple functions: it captures images for visual output, enables augmented reality features, and simultaneously provides visual flow data for motion detection and drift correction. This multi-functionality justifies the added complexity by extracting motion correction capabilities from an existing component rather than adding dedicated sensors.
Solution Approach 2:
The system uses its own camera, which is already present for other purposes, to correct the drift from the accelerometer. The camera's visual flow analysis serves the dual purpose of maintaining the display content and correcting motion detection accuracy, making the system self-correcting without requiring external correction devices.
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
This approach enhances the accuracy and reliability of motion detection, reducing drift and improving user experience in applications that rely on precise position and orientation control, such as gaming and augmented reality.
Implementation Method 1
A typical accelerometer is a small micro electro-mechanical systems (MEMS) device comprising a sprung cantilever beam with a mass supported at the free end of the beam. Under the influence of an external acceleration (e.g. an acceleration of the apparatus in which the accelerometer is provided), the mass deflects from a neutral position.
Implementation Method 2
a video camera operable to capture successive images of a part of the real environment around the apparatus
Implementation Method 3
the hardware motion detector comprises an acceleration detector and an integrator for integrating an output of the acceleration detector to generate velocity data indicative of velocity of movement of the apparatus
Data Source
Figure 1A~1B
Figure 2
Figure 3
AI summary
A portable data processing apparatus having at least one data processing function which depends on detected motion of the apparatus comprises a video camera operable to capture successive images of a part of the real environment around the apparatus; a video motion detector operable to detect motion of the apparatus by analysis of image motion between pairs of captured images; a hardware motion detector operable to detect motion of the apparatus, whereby the data processing function depends on motion detected by the hardware motion detector; and a controller operable to adjust the operation of the hardware motion detector if the motion detected by the video motion detector and the motion detected by the hardware motion detector differ by at least a threshold difference.