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  3. KNOWLEDGE AND DATA ENGINEERING
  4. Markerless Human–Manipulator Interface Using Leap Motion With Interval Kalman Filter and Improved Particle Filter
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Category: Knowledge and Data Engineering Projects
By MTech Projects
MTech Projects
15.May
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Markerless Human–Manipulator Interface Using Leap Motion With Interval Kalman Filter and Improved Particle Filter

PROJECT TITLE :

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

ABSTRACT:

The aim of this paper is to propose a completely unique markerless human-robot interface, that springs from the concept that the manipulator copies the movements of human hands. With this technique, one operator could management dual robots through each his or her hands in an exceedingly contactless and markerless atmosphere. So as to obtain the position and orientation of human hands in real time, a sensor referred to as leap motion (LM) is utilized in this paper. However, because of the tracking errors and noises of the sensor, the measurement errors increase with time. So, interval Kalman filter (IKF) and improved particle filter (IPF) are used to estimate the position and the orientation of the human hands, respectively. Furthermore, so as to avoid the perceptive limitations and also the motor limitations, that prevent the operator from winding up the high-precision experiment, a modification of adaptive multispace transformation (AMT) method is raised to help the operator to work out the posture of the manipulator. The greatest strength of our technique is that it is totally contactless and could estimate the create of the human hands accurately and stably while not any help 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 simply and successfully management robots with this human-manipulator interface.

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