Coordinated task execution by humanoid robot

This paper presents a framework for the coordinated task execution by a humanoid robot. To execute given tasks, various sub-systems of the robot need to be coordinated effectively. The goal of our paper is to develop the framework which makes it possible to interact with humans while executing various tasks in daily life environments. A script is used as a tool for describing tasks to easily regulate actions of the sub-systems while the robot is performing the task. The performance of the presented framework is experimentally demonstrated as follows: A mobile robot, as the platform of the task execution, recognizes the designated object. The object pose is calculated by performing model-based object tracking using a particle filter with back projection-based sampling. An approach proposed by Kim et al. is used to solve a human-like arm inverse kinematics and then the control system generates smooth trajectories for each joint of the humanoid robot. The mean-shift algorithm using bilateral filtering is also used for real-time and robust object tracking. The results of our implementation show the robot can execute the task efficiently in human workspaces, such as an office or home.