Early application of myoelectric prosthetic hand to children with congenital upper limb deficiency have been shown to be effective in acquiring familiarity with prosthetic hand and promoting movements using both hands. However, a robotic hand for prosthetic hand for infant is required to have a weight and size smaller than that of the infant's hand, also requires skill in the hand. These are in a trade-off relationship with each other. In addition, in order to reduce the cost of prosthetic hand and realize smooth application of prosthetic hand, a robot hand that can be used with a wide range of defects is required. In this study, we proposed a mechanism for a robotic hand of a myoelectric prosthetic hand for infants using a bevel gear and a DC motor. By using this mechanism, we have developed a lightweight and practical robotic hand that can be used with a wide range of defects. In addition, the gripping performance improved by searching for the shape of the finger parts of the robotic hand. Furthermore, we confirmed the effectiveness of the robotic hand by applying the developed robotic hand to infants with congenital upper limb defects.

In recent years, the use of drones has been advancing in various fields. In particular, attention is focused on autonomous drones that do not require a driver. However, autonomous drones need to use external information acquired by sensors to control flight so that the drone does not crash or become incapable of performing missions. In drones, it is important to consider the effects of wind-induced attitude changes, especially crashes, as well as preventing approach and collision with structures. However, as far as the author knows, path planning considering the influence of wind has not been announced so far. Therefore, we propose a method for path planning that avoids windy areas that have a large effect on drones. In this study, it is assumed that the drone can measure the current position and the wind direction and speed at that point. Based on that information, Model Predictive Control (MPC) performs path planning that predicts the wind condition around the drone and avoids windy areas. In this paper, we explain the wind prediction model and the setting of wind constraints for MPC. We also conducted an autonomous flight simulation in a windy environment to verify the effectiveness of the proposed method.

We are building a system that can automatically determine the bowing and fingering parameters for our anthropomorphic robot to perform the violin. We adopt the reinforcement leaning with ε-greedy policy, in which a neural network is embedded as a value function. This paper presents simulation results for determining the bow speed and the bowing-direction under the constant bow-force condition. Effects of the discount factor γ and the exploring rate ε on the bowing motion are investigated, while the previous study focused only on the discount factor. Simulation results suggests that by choosing appropriate values for the parameters, we can obtain the bowing parameters with higher reward values than the previous report, which means that the robot can produce sounds close to the target.

This paper proposes a grasping stiffness control method using a multi-fingered robot hand. This method does not need any information of a grasped object, such as geometry and attitude. The grasping stiffness is derived from geometrical constraints including rolling contact between a multi-fingered robot hand and a grasped object. To estimate the grasping stiffness without the use of external sensors, a contact point position of each fingertip is estimated by a relative relationship between the initial contact position and a virtual object frame. The proposed method is designed so that the desired grasping stiffness optimally transforms into a joint stiffness, and the desired joint stiffness is realized through each joint angle control. Finally, the usefulness of the proposed method is demonstrated through several numerical simulation results.

We propose an autonomous mobile robot Butsukusa, which describes its observations and internal states during the looking-around task. The proposed robot observes the surrounding environment and moves autonomously during the looking-around task. This paper examined several language generation systems based on different observation and interaction patterns to investigate better communication protocol with users.

In recent years, home medical care has been promoted, and it is desired to develop a machine that facilitates ankle range of motion training. Adjusting the stiffness of the brace for rehabilitation facilitates the setting of training goals determined between the patient and the practitioner. In this study, we are developing an ankle rehabilitation machine that controls the compliance of pneumatic artificial muscles arranged in an antagonistic Placement. In this paper, we confirm that the control performance is improved by Highly Durable Straight Fiber type pneumatic Artificial Muscles, and examine the stiffness control performance of the ankle joint rehabilitation machine.