As the possible applications for personal robots increase and involve more complicated environments and tasks, they need more appropriate control architectures. Previous control architectures have fixed configurations that are optimized for specific applications or with limited flexibility. Consequently, they fail to provide the flexibility needed for various robot kinematical configurations as well as various tasks. To this end, we propose a new task-based control architecture called "supervised hybrid architecture (SHA)". SHA is based on supervised organization and distributed arbitration of hybrid controls of reconfigurable deliberative and reactive modules. It is composed of upper level hybrid control for high-level intelligence to interact with human and to plan tasks, as well as lower level hybrid control to allow low-level intelligence for prompt reaction in each robot configuration module. Through these double layers of the hybrid controller, we could provide the flexibility needed for so many different kinematical configurations and tasks. In addition, it is very easy to add or remove robot configuration modules. The proposed architecture are implemented and tested to show how it works successfully.

A method is proposed to control the tip of a flexible multilink manipulator. The external sensory feedback controller can be easily constructed in task-oriented coordinates (for example Cartesian coordinates) without complex calculation for inverse kinematics or inverse dynamics. To realize the control method, a reduced-order approximate Jacobian which is formed by the motion of both rigid and flexible modes of the manipulator is introduced. The effectiveness of the proposed control method based on the approximate Jacobian is proved by using L/sub 2/ stability theory. The practical usefulness of the method is demonstrated by some experimental results for a flexible two-link manipulator.>