Toshiba AI Technology Catalog

  • Operation and Control

Two-stage control learning technology for image-based control

Reduces work in the application of controls and systems through end-to-end learning that does not require design of image recognition processing.


  • Learns policy for controlling robots from input images.
  • Reduces labor by learning control policy from accumulated operation data by experts or simulation environments.
  • Achieves high accuracy control by learning a control policy and a policy for correcting the control simultaneously.

Applications



  • Automation systems in logistics, manufacturing, maintenance, and inspection facilities that use robots
  • Automated control in moving bodies (e.g., AGVs and drones)
  • Control assistance for defense, medical devices, etc.

Benchmarks, strengths, and track record



  • The control policy is not susceptible to the surrounding environments, and can be easily learned from simulation environments.
  • When simulation environments are not available, control policy can be learned from accumulated operations data by experts.