• Blog
  • NAOqi - Developer guide
    • Getting Started
    • Creating an application
    • Programming for a living robot
    • Other tutorials
    • Choregraphe Suite
    • SDKs
    • NAOqi APIs
    • qi Framework
    • Former NAOqi Framework
    • Simulators
  • Pepper - Documentation
    • Pepper - User Guide
    • Pepper - Developer Guide
  • Lessons
  • Downloads
    • Linux
    • Mac
    • Windows
Search options
Pepper (NAOqi 2.5)
Search options
Pepper (NAOqi 2.5)
  • NAOqi - Developer guide
    • Getting Started
    • Creating an application
    • Programming for a living robot
    • Other tutorials
    • Choregraphe Suite
    • SDKs
    • NAOqi APIs
    • qi Framework
    • Former NAOqi Framework
    • Simulators
  • Pepper - Documentation
    • Pepper - User Guide
    • Pepper - Developer Guide
  • Lessons
  • Downloads
    • Linux
    • Mac
    • Windows
  • Blog

# Research & Innovation

The Artificial Intelligence Research Center (AIRC) is a team of scientists and engineers working together at Softbank Robotics on cutting-edge artificial intelligence (AI) systems to advance the state of the art in AI and robotics.

  • All(5)
  • Blog(5)
Blog

Learning a problem representation while exploring it

Learning a problem representation while exploring it
Learning algorithms generally need significant prior information on the task they are attempting to solve. This requirement limits their flexibility and forces engineers to provide appropriate priors at design time. A question then arises naturally: how can we reduce the amount of prior task information needed by the algorithm? Being able to answer this question could spark the development of algorithms with higher generalization potential, all the while reducing preliminary engineering efforts. If we want to discard any a priori knowledge about the task, we need the learning algorithm to efficiently explore and represent the space of possible outcomes it can achieve.
2021/02/24
Pepper closeup
Pepper QiSDK
Pepper closeup
Pepper (NAOqi 2.5)
NAO closeup
NAO⁶
  • Research & Innovation
Learning a problem representation while exploring it
Blog

Controlling Robots with Human Poses

Controlling Robots with Human Poses
A Research project about Pepper and NAO immersive teleoperation - A new immersive teleoperation solution based on Extreme Learning Machine (ELM), a Machine Learning technique, is introduced for Pepper and NAO robots. Immersive teleoperation is defined as a robot remote control that renders the operator the sensation of being inside the teleoperated environment and providing a feeling of being the robot itself. The solution is independent of other mapping approaches (e.g. inverse kinematics) and the user’s whole body is used for the robot control. Even with scarce training data, the solution returns satisfactory results in both precision and computational speed.
2020/12/31
Pepper closeup
Pepper QiSDK
Pepper closeup
Pepper (NAOqi 2.5)
NAO closeup
NAO⁶
  • Research & Innovation
Controlling Robots with Human Poses
Blog

CROWDBOT: Safe Navigation of Robots in Dense Crowds.

CROWDBOT: Safe Navigation of Robots in Dense Crowds.
CROWDBOT, an European Collaborative project enables robots to freely navigate and assist humans in crowded areas. - Today’s moving robots stop when a human, or any obstacle is too close, to avoid impact. This prevents robots from entering packed areas and effectively performing in a high dynamic environment. CROWDBOT aims to fill in the gap in knowledge on close interactions between robots and humans in motion.
2020/05/26
Pepper closeup
Pepper QiSDK
Pepper closeup
Pepper (NAOqi 2.5)
NAO closeup
NAO⁶
  • Research & Innovation
  • Navigation
CROWDBOT: Safe Navigation of Robots in Dense Crowds.
Blog

qiBullet

qiBullet
a Bullet-based simulator for the robots - qiBullet is a simulation tool enabling users to easily experiment with Pepper and NAO robots in virtual environments and gather accurate data.
2020/02/27
Pepper closeup
Pepper (NAOqi 2.5)
NAO closeup
NAO⁶
  • Github
  • Research & Innovation
qiBullet
Blog

CARESSES: smart and friendly robots for the elderly

CARESSES: smart and friendly robots for the elderly
An international partnership where SBRE puts forward Pepper to answer user specific needs - How can technology support the worldwide issue of the ageing populations and the complexity of human connections? SBRE committed into the CARESSES program to integrate a system that plans the robot's actions according to a relevant cultural knowledge base.
2019/05/17
Pepper closeup
Pepper (NAOqi 2.5)
  • Research & Innovation
  • Healthcare
  • Elderly
CARESSES: smart and friendly robots for the elderly
  • Japan
  • Europe/Middle East/Africa
  • Americas
  • China

Breadcrumb

  1. Home /
  2. Pepper (NAOqi 2.5) /
  3. Research & Innovation
  • Legal notices
  • Privacy Policy
  • Terms of use & Cookie settings
  • Support & Contact
Copyright @ SoftBank Robotics All rights reserved.