In this paper, an exact reshaping method for the motor dynamics of a flexible-joint robot is proposed using an integral manifold approach. Obtaining the exact model for both motor-side and linkside dynamics of a flexible-joint robot is difficult due to its under-actuated nature and complex dynamics. Despite the simple structure of the motor-side dynamics, they are difficult to model accurately for a flexible-joint robot due to motor disturbances, especially when speed reducers such as harmonic drives are installed. An integral manifold feedback control (IMFC) is proposed to reshape the motor dynamics. Based on the integral manifold approach, it is theoretically proved that the IMFC reshapes motor dynamics exactly even with bounded disturbances such as motor friction. The performance of the proposed IMFC is verified experimentally using a single degree-of-freedom flexible-joint robot under gravity conditions.

In this paper, an external torque estimation problem in one-degree-of-freedom (1-DOF) flexible-joint robot equipped with a joint-torque sensor is revisited. Since a sensor torque from the jointtorque sensor is distorted by two dynamics having a spring connection, i.e., motor dynamics and link dynamics of a flexible-joint robot, a model-based estimation, rather than a simple linear spring model, should be required to extract external torques accurately. In this paper, an external torque estimation algorithm for a 1-DOF flexible-joint robot is proposed. This algorithm estimates both an actuating motor torque from the motor dynamics and an external link torque from the link dynamics simultaneously by utilizing the flexible-joint robot model and the Kalman filter estimation based on random-walk model. The basic structure of the proposed algorithm is explained, and the performance is investigated through a custom-designed experimental testbed for a vertical situation under gravity.