18059214. DYNAMIC GRAVITY VECTOR ESTIMATION FOR MEMORY CONSTRAINED DEVICES simplified abstract (STMICROELECTRONICS S.r.l.)
Contents
- 1 DYNAMIC GRAVITY VECTOR ESTIMATION FOR MEMORY CONSTRAINED DEVICES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DYNAMIC GRAVITY VECTOR ESTIMATION FOR MEMORY CONSTRAINED DEVICES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DYNAMIC GRAVITY VECTOR ESTIMATION FOR MEMORY CONSTRAINED DEVICES
Organization Name
Inventor(s)
Federico Rizzardini of Settimo Milanese (IT)
Lorenzo Bracco of Chivasso (IT)
DYNAMIC GRAVITY VECTOR ESTIMATION FOR MEMORY CONSTRAINED DEVICES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18059214 titled 'DYNAMIC GRAVITY VECTOR ESTIMATION FOR MEMORY CONSTRAINED DEVICES
Simplified Explanation
The device described in the patent application includes processing circuitry coupled to memory, which estimates angular rate of change, determines a rotational versor, estimates a gravity vector, generates a dynamic gravity vector, estimates linear acceleration, and determines an acceleration versor and correction factor based on the acceleration data.
- The processing circuitry estimates angular rate of change and determines a rotational versor.
- The processing circuitry estimates a gravity vector based on the angular rate of change and the rotational versor.
- The processing circuitry generates a dynamic gravity vector based on the estimated gravity vector, a correction factor, and an estimated error in the estimated gravity vector.
- The processing circuitry estimates linear acceleration and determines an acceleration versor based on the acceleration data.
- The processing circuitry determines the correction factor based on the linear acceleration.
- The processing circuitry estimates the error in the estimated gravity vector based on the acceleration versor.
Potential Applications
This technology could be applied in:
- Inertial navigation systems
- Virtual reality and augmented reality devices
- Robotics for motion sensing and control
Problems Solved
This technology helps in:
- Improving accuracy of motion sensing
- Enhancing orientation tracking in devices
- Providing more reliable data for navigation systems
Benefits
The benefits of this technology include:
- Increased precision in motion tracking
- Enhanced user experience in virtual and augmented reality applications
- Improved efficiency in robotics and navigation systems
Potential Commercial Applications
The potential commercial applications of this technology could be in:
- Consumer electronics
- Aerospace and defense industries
- Healthcare for monitoring and tracking movements
Possible Prior Art
One possible prior art for this technology could be:
- Existing inertial measurement units used in aerospace and defense applications
Unanswered Questions
How does this technology compare to existing motion sensing technologies in terms of accuracy and reliability?
This article does not provide a direct comparison with existing motion sensing technologies to assess accuracy and reliability.
What are the potential limitations or challenges in implementing this technology in real-world applications?
The article does not address the potential limitations or challenges that may arise in implementing this technology in practical, real-world scenarios.
Original Abstract Submitted
A device includes a memory and processing circuitry coupled to the memory. The processing circuitry, in operation: estimates an angular rate of change and determines a rotational versor based on the rotational data; and estimates a gravity vector based on the angular rate of change and the rotational versor. The processing circuitry generates a dynamic gravity vector based on the estimated gravity vector, a correction factor and an estimated error in estimated gravity vector. The processing circuitry estimates a linear acceleration and determines an acceleration versor based on the acceleration data, and determines the correction factor based on the linear acceleration. The processing circuitry estimates the error in the estimated gravity vector based on the acceleration versor.
