Posts Taged ceatec

Preferred Networks unveils a personal robot system at CEATEC Japan 2018, exhibiting fully-autonomous tidying-up robots

Oct. 15, 2018, Tokyo Japan – Preferred Networks, Inc. (PFN, Headquarters: Chiyoda-ku, Tokyo, President and CEO: Toru Nishikawa) will unveil a fully-autonomous tidying-up robot system, which is currently under development, at the CEATEC Japan 2018 exhibition held in Makuhari Messe near Tokyo. A technical demonstration of the system will be given at the event.

PFN is developing technology to create a society where robots can actively support our daily living activities. Unlike in controlled and regulated environments like factories, robots in the home need to respond flexibly to dynamic and complex situations and communicate naturally with humans.

At its exhibition booth (A060), PFN will demonstrate the new robot system using HSRs (Human Support Robots) developed by Toyota Motor Corporation and showcase their ability to keep a cluttered room neat and tidy. This has been difficult to achieve using conventional technologies based on object recognition and robot control. The deep learning-based robots can recognize various scattered household items like clothes, toys, and stationery, grasp and place them in their designated locations. In the demonstration, PFN will also show that these cleaning robots can be controlled intuitively through verbal and gestural instructions.

For technical details, please visit the website.


The fully-autonomous tidying-up robot system has been awarded the Semi-Grand Prix in the Industry/Market category at CEATEC Award 2018, which recognizes innovative technologies, products, and services from among a large number of exhibits at CEATEC JAPAN 2018.


  • PFN exhibition booth

・Dates/time:10:00–17:00 Oct. 16–19, 2018

・Location:Booth A060, Total Solutions Area, International Exhibition Hall 2

・Exhibit:Technical demonstration of personal robots “fully-autonomous, tidying-up robot system” (first public exhibition)


In addition, PFN President and CEO Toru Nishikawa will make a keynote speech entitled “Robots for Everyone” on the opening day of the CEATEC exhibition. As well as introducing the outlook on future technologies, he will explain how PFN is applying cutting-edge technologies of machine learning, deep learning, and robotics to solve real-world problems.

  • CEATEC Keynote Future
  • ・Date/Time: 12:30~13:15 Tuesday on Oct. 16, 2018・Location:Convention Hall, International Conference Hall, Makuhari Messe・Speaker:Preferred Networks President and CEO Toru Nishikawa・Title/outline:”Robots for Everyone”The possibilities of robots are rapidly expanding thanks to the advancement of machine learning technology. Fusing the machine learning technology with robotics is essential for making robots that can flexibly respond to unexpected situations and execute various tasks like a human. Soon, we will begin to see an increasing number of robots helping to perform tasks in many places, working alongside humans. As well as introducing the current technology and PFN’s new initiative, President Nishikawa will provide insight into how we can leverage technology in the new era of these kinds of robots and the outlook on future technologies.

Preferred Networks releases deep learning-based, high-precision, visual inspection software


The software will make it possible to construct an inspection system quickly and inexpensively with minimal training datasets


Oct. 11, 2018, Tokyo Japan – Preferred Networks, Inc. (PFN, Headquarters: Chiyoda-ku, Tokyo, President and CEO: Toru Nishikawa) has developed Preferred Networks Visual Inspection,  high-precision, visual inspection software based on deep learning technology. PFN will start licensing the software to partner companies in December 2018. We will announce the new software at a new product seminar (N3-5) on Thursday Oct.18 during the CEATEC Japan 2018 exhibition held in Makuhari Messe near Tokyo.

The use of machine learning and deep learning technologies is spreading rapidly in many areas including the manufacturing floor. However, existing visual inspection systems based on deep learning require as many as several thousand images for training, as well as engineers to annotate the considerable number of images to facilitate the training process. Poorly explained inspection results are also among other issues that have been tackled.

In order to solve these problems, PFN has utilized its technical know-how acquired through the development of the deep learning framework Chainer(TM) and applications of deep learning to our main business domains – transportation systems, manufacturing, and bio-healthcare – to develop the Preferred Networks Visual Inspection.

  • The main features of Preferred Networks Visual Inspection:
  1. An inspection line can be set up with a small amount of training data (as few as 100 images of normal products and 20 images of defective products)
  2. Plastic, metal, cloth, food, and other materials with various shapes can be handled
  3. Results are well-explained through visualized anomalies such as scratches, foreign objects, and stains
  4. Training is made easy even for non-engineers with intuitive user interfaces


Preferred Networks Visual Inspection consists of a training support tool and CPU-based defect detection software. Depending on requirements, our licensed partners will install a combination of system components which include training workstations, inspection PCs, photographing equipment, UIs for visualization and operation. GPU-based, fast detection software is also available as an option.

The new product will enable users to build an easy-to-use and highly reliable auto-inspection system at a low cost in a short period of time. This product can be introduced with ease to the manufacturing lines which have been difficult to automate by existing products due to their high costs and inflexibility. In addition, defects are visualized so that its results can be easily explained. This is useful for passing down inspection skills and sharing knowledge with others in the company.

Comparison of Preferred Networks Visual Inspection and the existing solutions

  • New product announcement

PFN will announce Preferred Networks Visual Inspection at a New Technologies and Products Seminar (N3-5) entitled “Visual inspection system and picking robot solution based on deep learning” at CEATEC Japan in Makuhari Messe.


PFN will continue to promote practical applications of machine learning and deep learning technologies in the real world.