2005 · 154 citations · 24 references
EngineeringComputer ScienceRobotics EngineeringHumanoid RoboticsRobot KinematicsRoboticsHuman-robot Interaction DesignHuman-robot Interaction EvaluationHumanoid Robot MorphologyMotion CapturePostureHuman Motion AnalysisHuman-robot Kinematic ModelingMotion Capture Performance EvaluationMotion Capture System DesignMotion SynthesisNatural MotionRobot Appearance DesignThree-dimensional Motion Capture
Humanoid robotics seeks to enable natural interaction, requiring investigation of how behavior and appearance influence human evaluation, so android motions must closely match human performance to avoid appearing strange. The study proposes a method to generate human‑like motions by mapping a human performer’s 3‑D appearance onto an android and assessing motion verisimilitude with motion capture. The method maps the performer’s 3‑D appearance onto the android and evaluates the resulting surface motions using a motion capture system. Compared to joint‑angle copying, this approach better handles the android’s differing kinematics and aligns perceived motion with the robot’s surface rather than hidden joints.
One of the main aims of humanoid robotics is to develop robots that are capable of interacting naturally with people. However, to understand the essence of human interaction, it is crucial to investigate the contribution of behavior and appearance. Our group's research explores these relationships by developing androids that closely resemble human beings in both aspects. If humanlike appearance causes us to evaluate an android's behavior from a human standard, we are more likely to be cognizant of deviations from human norms. Therefore, the android's motions must closely match human performance to avoid looking strange, including such autonomic responses as the shoulder movements involved in breathing. This paper proposes a method to implement motions that look human by mapping their three-dimensional appearance from a human performer to the android and then evaluating the verisimilitude of the visible motions using a motion capture system. This approach has several advantages over current research, which has focused on copying a person's moving joint angles to a robot: (1) in an android robot with many degrees of freedom and kinematics that differs from that of a human being, it is difficult to calculate which joint angles would make the robot's posture appear similar to the human performer; and (2) the motion that we perceive is at the robot's surface, not necessarily at its joints, which are often hidden from view.
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