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Fukano Haruhisa Jeff Brower

Companies

Fujitsu and Ritsumeikan are contributing to framework for fusion of robots and sensors.

The framework combines sensor data collection, machine and deep learning models for analysis, and feedback for mechanical robot control.


Signalogic is contributing to the SESS blueprint automated speech recognition (ASR) functionality.

A 20,000 word real-time vocabulary is being implemented on a pico ITX Atom board (quad-core, 3.5" x 3.5", 10 W) suitable for

Ritsumeikan's food prep and production use cases, as well as a range of robotics use cases in manufacturing, production, agriculture, and retail.

The implementation includes robust audio noise processing to deal with background and robot mechanical noise.

Challenges

Robotics is an important tool for achieving the SDGs. Workers will be able to focus on decent work and new innovation by improvement of labor productivity using robot, as a result, they can move toward new economic growth. However, there are industries where it is difficult to apply current robotics. For example, agriculture, restaurant, food factory, etc.. The challenges current robotics faces in these industries are

  • Objects with diverse shapes, flexibility, and frictional properties
  • Uncertain environment
  • High-mix small-lot production

Solutions

Ritumeikan and Fujitsu research and develop enhancement of cognitive ability to solve these challenges. The features are the following three points.

  • Sensor-rich technology for multi-dimensional data acquisition
  • AI/IoT technology with force/contact information
  • IoT maintenance and inspection technology

This blueprint family provides open software stack which can implement above cognitive ability easy.

Results

The BP will allow robotic system integrators to easily implement systems that combine sensors and robots. We plan to enhance the following functions in 2022.

  • Analysis of sensor data and feedback to robot
  • Lightweight speech recognition to recognize "immediate and urgent" voice commands while protecting data privacy



LF Edge Project Collaboration

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