Robohub.org
 

ShanghAI Lectures: Hisato Kobayashi “AI-ish approach for complicated robot control”


by
05 December 2013



share this:

HisatoKobayashiGuest talk in the ShanghAI Lectures, 2009-11-12

If we try to describe any kinds of robot by mathematical models, they must be very complicated equations. Even, such robotic systems are categorized as a conventional dynamic system consist of positive definite inertia matrix, Coriolis’ force term, friction term, gravity term and so on, we cannot derive any authentic control scheme from such complicated nonlinear systems.

Of course, we can make a servo system for a joint control but we do not have any systematic control scheme for whole robots.

https://www.youtube.com/watch?v=6-n6meJXyQo

Hisato Kobayashi was born in Japan 1951. He graduated from Waseda University, he received both master degree and doctoral degree in electrical engineering from Waseda University in 1975 and 1978 respectively. During 1977-1982, he was a research associate of Tokyo University Agriculture and Technology. He joined Hosei University in 1982. He spent almost one year at Stuttgart University Germany 1988-1989 as an invited visiting researcher of Alexander Humboldt Foundatiion. He is now professor of Hosei University Tokyo, department of art and technology,he was president of Hosei University Research Institute, California. During 1998-2001, he was a visiting scholar of Stanford University and doing a joint project entitled “Sleep Smart Project.” He was Editor in Chief of Advanced Robotics, which was issued by Robotics Society in Japan and published by Brill Publisher in Holland. He was elected as fellow of IEEE in 2002. His research interests cover control theory, mechatronics systems, robotics and health care systems.

The ShanghAI Lectures are a videoconference-based lecture series on Embodied Intelligence run by Rolf Pfeifer and organized by me and partners around the world.

The ShanghAI lectures have brought us a treasure trove of guest lectures by experts in robotics. You can find the whole series from 2012 here. Now, we’re bringing you the guest lectures you haven’t yet seen from previous years, starting with the first lectures from 2009 and releasing a new guest lecture every Thursday until all the series are complete. Enjoy!



tags: ,


Nathan Labhart Co-organizing the ShanghAI Lectures since 2009.
Nathan Labhart Co-organizing the ShanghAI Lectures since 2009.

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Developing active and flexible microrobots

  13 May 2026
This class of robots opens up possibilities for biomedical applications.

How to teach the same skill to different robots

  11 May 2026
A new framework to teach a skill to robots with different mechanical designs, allowing them to carry out the same task without rewriting code for each.

Robot Talk Episode 155 – Making aerial robots smarter, with Melissa Greeff

  08 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Melissa Greeff from Queen's University about autonomous navigation and learning for drones.

New understanding of insect flight points way to stable flapping-wing robots

  07 May 2026
The way bugs and birds flap their wings may look effortless, but the dynamics that keep them aloft are dizzyingly complex and difficult to quantify.

Robotically assembled building blocks could make construction more efficient and sustainable

  05 May 2026
Research suggests constructing a simple building from interlocking subunits should be mechanically feasible and have a much smaller carbon footprint.

Robot Talk Episode 154 – Visual navigation in insects and robots, with Andrew Philippides

  01 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Andrew Philippides from the University of Sussex about what we can learn from ants and bees to improve robot navigation.

Ultralightweight sonar plus AI lets tiny drones navigate like bats

  29 Apr 2026
Researchers develop ultrasound-based perception system inspired by bat echolocation.

Gradient-based planning for world models at longer horizons

  28 Apr 2026
What were the problems that motivated this project and what was the approach to address them?



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence