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We propose a brachiation robot named Brachiator. Brachiator is able to swing like a real gibbon. The limbs of Brachiatior are designed to be actuated through the wires. However, the elongation and slack of the wires often arise and make it difficult to estimate the joint angles accurately, which has to be resolved to attain more stable brachiation behavior. In this paper we introduce a vision system to improve brachiation behavior in real time. A stereo vision system is mounted on Brachiator that looks like a gibbon's face. We estimate errors between a model based trajectory and a real trajectory in implementation world from the images which the vision system captures during the brachiation behavior. Based on the vision-based error estimation as to the grasping position on the target branch, the trajectory of the behavior is adjusted in real time in order to realize successful brachiation behaviors. Experimental results showed that the proposed system reduced deviation of the grasping position of brachiation behavior as much as 43% compared with previous methods.

This paper proposes a system, which manages both efficiency and flexibility in the manufacturing system. It has been considered that a autonomous distributed system is superior to a centralized system in terms of fail-proof, expansion, load dispersion, flexibility, and the possibility of the evolution. However, it is difficult to manage both efficiency and flexibility according to conventional method in a autonomous distributed system. To solve the problem, we propose a method, where the carrier organizes the whole number of the carrier in the system, according to the volume of the task and the complexity of it. Also we evaluate the proposed method of self-organizing behavior by a multi-AGV autonomous system in the quantitative dynamic environment. It is shown that the system exhibits higher efficiency compared with the centralized system by introducing self-organizing in the quantitative dynamic environment.

This paper proposes a system, which manages both efficiency and flexiblity ill the AGV (Auto Guided Vehicle) transportation system. Generally, It has been considered that a distributed autonomous system is superior to a centralized system in terms of fail-proof, expansion, load dispersion, flexibility, and the possibility of the evolution. Especially, the most effective characteristic of an autonomous distributed system is a restoration behavior for the system performance. In this paper, to realize the behavior so as to restore the system performance on managing efficiency and flexibility, we propose the method, where each AGV organizes the whole number of the AGV in the system by self-organizing behavior through interaction in the local domain under the change of environment, and evaluate the efficiency which is defined as amount of transportation per an AGV. It is shown that the system exhibits autonomous restoration of the system performance and higher efficiency compared with the centralized system by introducing self-organizing in the dynamical environment.