Measuring task complexity of movement skill is an important factor to evaluate a difficulty of learning and/or imitating a task for autonomous robots. Although many complexity-measures are proposed in research areas such as neuroscience, physics, computer science, and biology, there have been little attention on the robotic tasks. To cope with measuring complexity of robotic task, we propose an information-theoretic measure for task complexity of movement skills. By modeling proprioceptive as well as exteroceptive sensor data as multivariate Gaussian distribution, movements of a task can be modeled as probabilistic model. Additionally, complexity of temporal variations is modeled by sampling in time and modeling as individual random variables. To evaluate our proposed complexity measure, several experiments are performed on the real robotic movement tasks.

In this paper, we are looking for requirements of software, hardware and application for use in network-based robots and also directions in building standardization and research activities by reviewing technical status of the robot industries developing robots. The questions are including awareness of RUPI(Robot Unifies Platform Initiative) activities, target market and applications, hardware specifications, software development technologies, and HRI(Human Robot Interaction). The RUPI committee creates standard and derives implementation software for network-based robots through industrial requirements as like of the results. Many robots have been developed and launched services based on RUPI 1.0 standards. Based on this achievement we are expanding RUPI standard to include thin and thick client robots. The results also show that which one is important and urgent technology in the sense of industrial robotic business.