Till date, various seven-degrees-of-freedom (7-DOF)robot arms have been developed globally. In general, the robot arms utilized in factories are required to possess speed, power, and accuracy. They are isolated from humans using a fence to ensure human safety. However, a home robot should work near humans at an appropriate speed without a fence. One approach to meeting this requirement involves the installation of various sensors on the robot to control and stop the robot safely even if a collision has occurred. However, a robot system is complicated and expensive. In order to give inherent safety to the robot, we should lighten the robot arm. In this study, a 7-DOF lightweight arm with a wide wrist-motion range is introduced. The weight of movable parts is approximately 2.87 kg. To achieve such properties, we propose the use of three mechanisms: a shoulder mechanism with hollow cylinders, a wrist mechanism with a wide workspace, and an integrated wrist and elbow mechanisms of high power. To verify its feasibility, a prototype of the robot is designed and developed. The experimental results demonstrate its powerful performance and wide workspace of the wrist.

Abstract This paper proposes a new methodology, Sliding Window-based Support Vector Regression (SW-SVR), for micrometeorological data prediction. SVR is derived from a statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data. Although SVR is superior to traditional learning algorithms such as Artificial Neural Network (ANN), it is difficult to choose the suitable amount of training data to build an optimum SVR model for micrometeorological data prediction. This paper revealed the periodic characteristics of micrometeorological data and evaluated SW-SVR can adapt the appropriate amount of training data to build an optimum SVR model automatically using parallel distributed processing. The future prediction experiment was conducted on air temperature of Sapporo, Tokyo, Hamamatsu, and Naha. As a result, SW-SVR has improved prediction accuracy in Sapporo, and Tokyo. In addition, it has reduced calculation time by more than 96% in all regions.

An information-presenting robot is expected to establish an appropriate spatial relationship with people. Drawing upon sociological studies of spatial relationships involving "F-formation" and "body torque," we examined the effect of a robot rotating its body on the reconfiguration of the F-formation arrangement. The results showed that a robot can change the position of a visitor by rotating its body. We also confirmed that to reconfigure the F-formation arrangement, it is more effective to rotate the whole body of the robot than only its head.

If robot systems are being deployed in real world settings with untrained users who happen to accidentally pass by or could leave at any moment in time, then this places specific demands on the robot system: it needs to secure and maintain the user's engagement. In this, a common and critical problem consists of entering into a `focused encounter'. It requires each interactional partner to closely react upon the other's actions on a very fine-grained level engaging in a stepwise and dynamic process of mutual adjustments. We report initial findings from a study in which we have developed a preliminary, simple solution to this problem inspired by work from Conversation Analysis. Using this as an instrument to explore the impact of a `contingent' (CE) vs. `non-contingent entry' (NCE), we find that users who enter into the interaction in a dynamic and contingent manner show a significantly different way of interacting with the robot than the NCE group.

In this paper we consider the development of a museum guide robot that has both autonomous and remotely controlled features. We focus on the capabilities such a robot could have to help focus the attention of a visitor on an object or artefact. Inspired by studies of social interaction, which investigate whether the robot could deploy "restarts" and "pauses" at certain moments in its talk to first elicit the visitor's attention/gaze towards the robot. We report an experiment where we deployed such a robot to interact with real visitors to a science museum. These experiments show that such a strategy does seem to have a significant impact on obtaining the visitor's gaze.