improving the brain machine interface so that robots understand human intentions is essential in expanding practical applications of robots. The main trend in BMI has been to transmit information from the human brain to the robot’s computer, but the research group of Dr. Mitsuo Kawato, director of the Computational Neuroscience Laboratories at the Advanced Telecommunications Research Institute International (ATR), has developed a robot that can learn by imitating humans.This robot is the CBi, a humanoid robot with a height of 155 cm and weight of 85 kg. Kawato and his colleagues have conducted many studies on reproducing brain activity in computers. The result of their accumulated research was the successful development of a computer system that, when a constant movement is repeated, automatically programs that movement so that it can be reproduced. When a human takes the CBi’s arm or leg and teaches it how to move, this system on the CBi enables it to automatically learn that movement. It is thus imitating human activity.
Controlling a robot today generally requires expert knowledge, making it virtually impossible for ordinary people to operate robots. With advances in the system developed by Kawato, however, general users will be able to control robots, and this could serve to accelerate the spread of their use.
The CBi has already learned such high-level movements as using a bat to hit a ball thrown by a human, and rolling a ball on its palm. Viewers were amazed with a public demonstration in January 2009 of the CBi hitting a thrown ball.
Flexible joints are another characteristic of the CBi. Gear mechanisms are used in most robot joints, but the CBi’s main joints use hydraulic cylinders. This enables smoother and more human-like movements than in conventional robots. The CBi is also equipped with high-level posture control with the use of a three-axis gyroscope and acceleration sensor, so that it keeps its feet and does not fall over easily even when pushed or shaken by humans.
The CBi is also at the leading edge of BMIs in which the computer understands brain activity. Its abilities were demonstrated in January 2008 when it showed that it could imitate a monkey. In a joint experiment between ATR and Duke University in the United States, Duke Professor Miguel Nicolelis and colleagues had a monkey walk on a treadmill, and then data of the monkey’s brain activity was sent in almost real time over the Internet to the CBi in Kawato’s laboratory. The CBi understood the movements of the monkey based on such data and walked in a similar way. When the movements of the CBi were displayed in front of the monkey walking on the treadmill, the monkey seemed to match its pace to that of the CBi, Nicolelis reported. The results of this experiment were viewed as a successful example of interactive BMI. (Keiichi Maeda)
Controlling a robot today generally requires expert knowledge, making it virtually impossible for ordinary people to operate robots. With advances in the system developed by Kawato, however, general users will be able to control robots, and this could serve to accelerate the spread of their use.
The CBi has already learned such high-level movements as using a bat to hit a ball thrown by a human, and rolling a ball on its palm. Viewers were amazed with a public demonstration in January 2009 of the CBi hitting a thrown ball.
Flexible joints are another characteristic of the CBi. Gear mechanisms are used in most robot joints, but the CBi’s main joints use hydraulic cylinders. This enables smoother and more human-like movements than in conventional robots. The CBi is also equipped with high-level posture control with the use of a three-axis gyroscope and acceleration sensor, so that it keeps its feet and does not fall over easily even when pushed or shaken by humans.
The CBi is also at the leading edge of BMIs in which the computer understands brain activity. Its abilities were demonstrated in January 2008 when it showed that it could imitate a monkey. In a joint experiment between ATR and Duke University in the United States, Duke Professor Miguel Nicolelis and colleagues had a monkey walk on a treadmill, and then data of the monkey’s brain activity was sent in almost real time over the Internet to the CBi in Kawato’s laboratory. The CBi understood the movements of the monkey based on such data and walked in a similar way. When the movements of the CBi were displayed in front of the monkey walking on the treadmill, the monkey seemed to match its pace to that of the CBi, Nicolelis reported. The results of this experiment were viewed as a successful example of interactive BMI. (Keiichi Maeda)
Source : sciencelinks
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