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A framework to generate a human-like arm motion of a humanoid robot using an Evolutionary Algorithm(EA)-based imitation learning is proposed. The framework consists of two processes, imitation learning of human arm motions and real-time generating of a human-like arm motion using the motion database evolved in the learning process. The imitation learning builds the database for the humanoid robot that is initially converted from human motion capture data and then evolved using a genetic operator based on a Principal Component Analysis (PCA) in an evolutionary algorithm. This evolution process also considers the minimizing of joint torques in the robot. The database is then used to generate humanoid robot's arm motions in real-time, which look like human's and require minimal torques. The framework is examined for humanoid robot to reach its arms for catching a ball. Additionally, the inverse kinematics problem to determine the final posture of 6-DOF robot arm with a waist for the task of catching a ball, is proposed.

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Abstract:The paper proposes 'Network-based Humanoid', that is, a humanoid endowed with its perception capability and intelligence by an external computer system connected with wireless network. The network-based humanoid is composed of a humanoid test-bed, an internal control system and an external computer system. The internal distributed control system is composed of two parts. One is responsible for motion control of the humanoid following commands from the external computer system while the motion control is done by a CAN-based distributed motor controller. The other is for real-time data transmission of image data, voice data, and sensor data for motion control by wireless network to the external computer system. The external computer system, a network-based distributed control system, processes the transmitted data, decides the final action command for the humanoid, and transmits the action command to the internal control system. A network-based humanoid, whose name is 'MAHRU', is developed successfully. The humanoid can walk using two legs with the maximum speed of 0.9 Km/h. It is noted that the humanoid can recognize faces, gestures of human beings in real-time, three-dimensional objects, and 100 voice words with the help of the external computer system connected through wireless network. And, the humanoid interacts with human beings via a stereo camera, a microphone, and force/torque sensors.