Development of a remote-brained humanoid for research on whole body action

In this paper, a second generation remote-brained humanoid robot is presented which is developed for research on whole body action. Humanoid robots are important as a platform for the integration of techniques and algorithms acquired from research on manipulators, legged robots and so on. And they have new problems such as how to acquire, memorize, select and carry out various motions which use their whole bodies efficiently. In order to do research on these problems, a good robot body, which has whole body and enough performance for walking and getting up when it falls down is necessary. At the same time, a powerful brain is necessary which can be evolved through the body. As a solution to these demands, remote-brained approach was proposed and several humanoid robots was developed. Using these robots, several researches were done. For example, a brain framework called BeNet, an action acquisition using GA and NN and so on. They were done using a simple wireless connection. Interface between robot brain and its body to concentrate on a high-level problem. However this interface limited actions the robot can do simultaneously. In this paper, this old interface is taken to the next step. New interface has multiple actuator control methods which are switched on demand, and an onbody microprocessor network which controls actuators, measures sensors and interacts with a brain. Finally a new humanoid robot is developed on this interface