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This article reports the pneumatic artificial muscles based on biomechanical characteristics of human muscles. A wearable device and a rehabilitation robot that assist a human muscle should have characteristics similar to those of human muscle. In addition, since the wearable device and the rehabilitation robot should be light, an actuator with a high power to weight ratio is needed. At present, the McKibben type is widely used as an artificial muscle, but in fact its physical model is highly nonlinear. Therefore, an artificial muscle actuator has been developed in which high-strength carbon fibres have been built into the silicone tube. However, its contraction rate is smaller than the actual biological muscles. On the other hand, if an artificial muscle that contracts axially is installed in a robot as compactly as the robot hand, big installing space is required. Therefore, an artificial muscle with a high contraction rate and a tendon-driven system as a compact actuator were developed, respectively. In this study, we report on the basic structure and basic characteristics of two types of actuators.

Many different types of pipeline installations exist, such as pipelines used in chemical plants, water pipes and gas pipes. All must be examined and maintained to prevent severe accidents through a program of continual pipe inspection and repair. Herein, we have developed a cylindrical crawler robot for pipe inspection. We propose a simple crawler robot steering principle along with verification tests. The prototype robot with the proposed steering mechanism was able to travel through all T-branch paths.

In recent years, attention has been increasingly devoted to the development of rescue robots that can protect humans from the inherent risks of rescue work. Particularly, anticipated is the development of a robot that can move deeply through small spaces. We have devoted our attention to peristalsis, the movement mechanism used by earthworms. A reinforcement learning technique used for the derivation of the robot movement pattern, Q-learning, was used to develop a threesegmented peristaltic crawling robot with a motor drive. Characteristically, peristalsis can provide movement capability if at least three segments work, even if a segmented part does not function. Therefore, we had intended to derive the movement pattern of many-segmented peristaltic crawling robots using Q-learning. However, because of the necessary increase in calculations, in the case of many segments, Q-learning cannot be used because of insufficient memory. Therefore, we devoted our attention to a learning method called Actor-Critic, which can be implemented with low memory. Because Actor-Critic methods are TD methods that have a separate memory structure to explicitly represent the policy independent of the value function. Using it, we examined the movement patterns of six-segmented peristaltic crawling robots.

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