Session Program

Abstract - In recent years, the development of nursing and welfare robots intended for people with disabilities and elderly has been advanced. The research of the method to transmit human intentions to the robot by using the biological information of the operator is proceeding. In this research we propose a method to perform the locomotive control of omnidirectional wheelchair by a gaze instruction system based on the human intention estimated by using fuzzy reasoning, and an instruction system using electromyogram(EMG) of operator's forearm and fuzzy reasoning. We performed the operating experiment using gaze and EMG measurement device, and we confirmed that the operator can perform the moving control of wheelchair according to his/her instructions.

Abstract - Total Hip Arthroplasty (THA) recently becomes more famous in Japan. The number of operations is increasing more and more because of longevity. THA requires subjectivity judgement of surgeons due to lack of proper measurement system for surgery. Especially, inserting artificial femoral joint is important for clinical outcome (e.g., pain, and loosening.). In addition, femoral stem which is one of the artificial joints, has a shape fitting to femur bone. Therefore, the insertion angle strongly relates the fixation degree of artificial joint. This study aims to specify the curve shape of medial proximal part of stem by measuring the curve with ultrasound device. This study develops five probes with small size which enables us to embed the probes into inside stem. The probes measure reflected echoes from boundary of the femur contour, then the propagated time of the echo was converted into the distance from the surface of the probes and the femur contour by using ultrasound velocity. The experiments were performed with two femur models. As a result, the proposed system could show the contour which is corresponding with real shape. We indicated usefulness of the method using ultrasound proves for measuring a curve stem inside.

Abstract - Conventional studies have suggested that emotion representation of a robot affects human action decision in human-robot communication. The influence of emotional expression of the robot to the human decision-making can be represented by a simple fuzzy inference model. However, they often use emotion expression by mimicking human facial expression on a robot, however, emotion expression by no facial expression but the motion of limbs, LEDs, and audios of a humanoid robot has not been studied for the evaluation of human action decision effect. This study proposes an experiment design based on a finite iterated prisoner's dilemma game with a humanoid robot that shows multimodal emotion expression during the game in order to investigate the effect of the emotion expression of the robot on cooperative and/or selfish action decision making of the human individuals. The experimental results are analyzed to show the influence of the decision making and impression on the robot of the people according to the emotional expression of the humanoid robot.

Abstract - Adobe Illustrator provides many tools for a user to create art works. The tools also provide many parameters or options that the user can tune up or select. This study focuses on black-and-white drawings (``Sumi-e'' or ``Suiboku-ga'' in Japanese) on Adobe Illustrator. In order to create black-and-white drawings, the user usually has to select a proper brush from preset brushes Adobe Illustrator provides. But the selections are difficult for the user, especially beginners. This paper proposes a supporting plug-in tool for the user to decide and apply the proper brush. The plug-in can accept an onomatopoeic utterance input which expresses the user's own imagenation or impression of the brush. Onomatopoeia is well known as a useful figurative expression for Japanese people to describe their own imagenation or impression for something. This paper reports the configuration of the plug-in and illustrated some examples of black-and-white drawings created by using the plug-in.

Abstract - With the growth of robot technology, more robots are being designed to support learning. Most studies in the field have focused on robot behavior, with only a few studies focusing on robot utterances. Correspondingly, the manner in which such utterances affect learning is poorly understood. This study investigates the effects of collaborative learning wherein a robot encourages a learner. We conducted an experiment to compare the learning effect in three groups. In the first group, learning was conducted with a robot that supplied praises using onomatopoeia, i.e., the representation of an object or state based on the sounds associated with it. In the second group, a robot supplied praises using adjectives or adverbs. In the third group, a robot supplied praise without using onomatopoeia, adjectives, or adverbs. The results of this study suggest that collaborative learning using the first or third method is more effective than that involving adjective/adverb communication.

Abstract - "Are you a werewolf?" is one of the most popular communication games and is played globally. The AIWolf Project developed an agent, named "the AIWolf," that can play "Are you a werewolf?". An AIWolf utters its thoughts using an AIWolf Protocol. As it is difficult for humans to understand the AIWolf Protocol, translation into natural language is required when human players are involved. However, the conventional method of translation uses a word-to-word method, creating the impression that the utterances have been generated by a machine. This study aimed make the utterances of AIWolf sound more human. The authors set the target that a human player would be unable to distinguish human speech from that generated by AIWolves (the Turing test). The authors define the situation as the maximum value of humanity. The output of translated AIWolf Protocol was paraphrased using data from Werewolf BBS Logs. This study considers making the utterances of AIWolf sound more human using Werewolf BBS Logs and a possibility assignment equation with fuzzy sets. In this paper, an experiment was conducted to confirm whether paraphrasing the utterances of AIWolf using Werewolf BBS Logs for human-like speech is useful or not. It was shown that the experimental method produced slightly more human-like speech than the conventional method.