NAO humanoid robot

The strength of the NAO humanoid robot is discussed with several challenges in the arena of human portrait and sketch drawing. These challenges include extracting feature points from the input image, defining these points with respect to end effector, finding the inverse kinematics solution and designing a visual feedback system. This paper mainly addresses the fundamental issue of defining a relationship between the points of the image plane and NAO end effector position. This relationship enables NAO to perceive points of image plane with respect to its body coordinate system. Three different techniques based on the principles of fundamental matrix, pseudo inverse and Artificial Neural Network based regression analysis are applied to handle the calibration difficulties on NAO robot. A comprehensive study on sample points collected from NAO end effector position and corresponding image points has been made to understand the effectiveness of each technique. The degree of performance ability of each technique has been measured using time complexity, and mean square error metrics. The paper proposed 3 novel techniques to calibrate humanoid camera plane to its end-effector position. The solution is generalized consider the experimental setup is same.Extensively error analysis and time complexity analysis is performed to evaluate each proposed technique.Proposed techniques are computationally sound and require only few points (4 points) to calibrate the system. The error involved in calibration is also very less.