Masatake Higashi

The Extraction of Symbolic Postures to Transfer Social Cues into Robot

At present, the inclination of robotic researchers is to develop social robots for a variety of application domains. Socially intelligent robots are capable of having natural interaction with a human by engaging in complex social functions. The challengeable issue is to transfer these social functions into a robot. This requires the development of computation modalities with intelligent and autonomous capabilities for reacting to a human partner within different contexts. More importantly, a robot needs to interact with a human partner through human-trusted social cues which create the interface for natural communication. To execute the above goals, robotic researchers have proposed a variety of concepts that are biologically-inspired and based on other theoretical concepts related to psychology and cognitive science. Recent robotic research has been able to achieve the transference of social behaviors into a robot through imitation-based learning (Ito et al., 2007) (Takano & Nakamura, 2006), and the related learning algorithms have helped in acquiring a variety of natural social cues. The acquired social behaviors have emphasized equipping robots with natural and trusted human interactions, which can be used to develop a wide range of robotic applications (Tapus et al., 2007). The transference of a variety of skills into a robot involves several diminutive and imperative processes: the need for efficient media for gathering human motion precisely, the elicitation of key characteristic of motion, a generic approach to generate robot motion through the key characteristics of motion, and the need for an approach to evaluate generated robot motions or skills. The use of media for amassing human motions has become a crucial factor that is very important for attaining an agents motion within deficit noisy data. Current imitation research has explored ways of simulating accurate human motions for robot imitations through a motion capture system (Calinon & Billard, 2007(a)) or through image processing techniques (Riley et al., 2003). A motion capture system provides accurate data that is quieter than image processing techniques (Calinon & Billard, 2007(b)).

Integration of CAD/CAM systems in automotive body engineering

Abstract This paper describes examples of CAD and CAM in automotive body engineering process at TOYOTA Motor Corp. Philosophy of integrating systems and importance of improvement of design quality are discussed with examples.

Development of a social learning mechanism for a humanoid robot

A main purpose of humanoid robotic research is to develop a socially interactive robot by providing for a certain degree adaptability and flexibility in order to endow the robot with natural interactions with humans. In this paper, a social learning mechanism is proposed for enabling a humanoid robot to learn social behaviors through imitation. To achieve this goal, a novel imitation algorithm is proposed for transferring human social behaviors into a robot in real time. This approach considers the characteristic of motions for extracting symbolic postures, which consists of changing the points of motion directions. Reinforcement learning is utilized for extracting optimal symbolic postures and for incorporating the divisional cubic spline interpolation for generating a robotpsilas social behaviors through symbolic postures. In our experiment, we attempt to transfer three social cues: a ldquopointing gesture,rdquo a gesture for ldquoexplaining something attractively,rdquo and a gesture for expressing ldquoI donpsilat know.rdquo The experimental results confirmed the accuracy of the robot motion generation through the proposed mechanism for transferring natural social behaviors.