18020552. MOTION LEARNING APPARATUS, MOTION LEARNING METHOD, MOTION ESTIMATION APPARATUS, MOTION ESTIMATION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM simplified abstract (NEC Corporation)

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MOTION LEARNING APPARATUS, MOTION LEARNING METHOD, MOTION ESTIMATION APPARATUS, MOTION ESTIMATION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM

Organization Name

NEC Corporation

Inventor(s)

Hiroaki Inotsume of Tokyo (JP)

MOTION LEARNING APPARATUS, MOTION LEARNING METHOD, MOTION ESTIMATION APPARATUS, MOTION ESTIMATION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18020552 titled 'MOTION LEARNING APPARATUS, MOTION LEARNING METHOD, MOTION ESTIMATION APPARATUS, MOTION ESTIMATION METHOD, AND COMPUTER-READABLE RECORDING MEDIUM

Simplified Explanation

The motion learning apparatus described in the patent application includes a motion analyzing unit and a learning unit. The motion analyzing unit analyzes the motion of a mobile object based on mobile object state data and generates motion analysis data. The learning unit learns a model for estimating the motion of the mobile object in a first environment using motion analysis data generated in the first environment and motion analysis data generated in respective second environments.

  • The motion learning apparatus analyzes the motion of a mobile object and learns a model for estimating its motion in different environments.
  • The motion analyzing unit uses mobile object state data to generate motion analysis data.
  • The learning unit uses the motion analysis data from different environments to learn a model for estimating the motion of the mobile object in a first environment.

Potential applications of this technology:

  • Robotics: The motion learning apparatus can be used in robotics to analyze and learn the motion of robots in different environments, allowing them to adapt and navigate more effectively.
  • Sports training: The apparatus can be used in sports training to analyze and learn the motion of athletes, providing valuable insights for improving performance and preventing injuries.
  • Virtual reality: The technology can be applied in virtual reality systems to analyze and learn the motion of virtual objects, enhancing the realism and immersion of the virtual environment.

Problems solved by this technology:

  • Adaptation to different environments: The motion learning apparatus allows mobile objects to adapt their motion based on the analysis and learning of different environments, improving their performance and efficiency.
  • Motion estimation accuracy: By learning a model for estimating motion using data from different environments, the apparatus can improve the accuracy of motion estimation for mobile objects.

Benefits of this technology:

  • Enhanced performance: By analyzing and learning the motion of mobile objects in different environments, the technology can enhance their performance and efficiency.
  • Adaptability: The motion learning apparatus enables mobile objects to adapt their motion based on the specific environment they are in, improving their ability to navigate and interact with their surroundings.
  • Improved motion estimation: By learning a model for motion estimation using data from different environments, the technology can improve the accuracy of motion estimation for mobile objects.


Original Abstract Submitted

A motion learning apparatus includes: a motion analyzing unit configured to analyze motion of a mobile object based on mobile object state data, and generating motion analysis data; and a learning unit configured to learn a model for estimating the motion of the mobile object in a first environment, using first motion analysis data generated in the first environment and second motion analysis data generated in respective second environments, and furthermore, a motion estimation apparatus includes: an environment analyzing unit configured to analyzing a first environment based on environment state data indicating a state of the first environment, and generating environment analysis data, and an estimation unit configured to estimate motion of a mobile object in the first environment by inputting the environment analysis data to a model.

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