Markerless Human-Manipulator Interface Using Leap Motion With Interval Kalman Filter and Improved Particle Filter

The aim of this paper is to propose a novel markerless human-robot interface, which is derived from the idea that the manipulator copies the movements of human hands. With this method, one operator could control dual robots through both his or her hands in a contactless and markerless environment. In order to obtain the position and orientation of human hands in real time, a sensor called leap motion (LM) is employed in this paper. However, because of the tracking errors and noises of the sensor, the measurement errors increase with time. Therefore, interval Kalman filter (IKF) and improved particle filter (IPF) are used to estimate the position and the orientation of the human hands, respectively. Furthermore, in order to avoid the perceptive limitations and the motor limitations, which prevent the operator from carrying out the high-precision experiment, a modification of adaptive multispace transformation (AMT) method is raised to assist the operator to determine the posture of the manipulator. The greatest strength of our method is that it is totally contactless and could estimate the pose of the human hands accurately and stably without any assistance from markers. A series of experiments have been conducted to verify the human-manipulator interface system, and the results show that the system is indeed of high availability and fault tolerance in teleoperation, which means even a novice can easily and successfully control robots with this human-manipulator interface.