Saeed Shiry

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Controlling a biped robot with a high degree of freedom to achieve stable and straight movement patterns is a complex problem. With growing computational power of computer hardware, high resolution real time simulation of such robot models has become more and more applicable. This paper presents a novel approach to generate bipedal gait for humanoid(More)
Mobile robot localization is taken into account as one of the most important topics in robotics. In this paper, the localization problem is extended to the cases in which estimating the position of multi robots is considered. To do so, the Joint Probabilistic Data Association Filter (JPDAF) approach is applied for tracking the position of multiple robots.(More)
Detecting motion of objects in images, while the camera is moving, is a complicated task. In this paper, we propose a novel method to effectively solve this problem by using Neural Networks and Kalman Filter. This technique uses movement parameters of camera to overcome problems caused by error in image processing outputs. We implemented this technique in(More)
The slave robot in this research is a 1-DOF piezo actuator which includes hysteresis nonlinearity. Nonlinear hysteresis behavior makes robot control a complex task. In this research, the nonlinear and uncertain dynamics of the slave robot has been considered through the teleoperation control loop. LuGre friction model is used as the estimator of the(More)
This paper describes the use of wavelet entropy as a feature extractor for robust classification of cracks in sewer pipe structures. Video image data was acquired using an infrared camera in an experimental sewer pipe setup. Video frames were partitioned into 64 * 64 pixel sections. 1,885 'crack' and 1,675 'clean' (non-crack) sections were manually(More)
—This paper describes the use of a novel method of feature extraction for visual sensor processing. An application to crack detection by a sewer maintenance robot equipped with an infra-red camera is described. A space-frequency distribution 'signature' is generated via a three step process involving; space-frequency decomposition, density function(More)
Human can perform object recognition with high accuracy under a variety of object rotations and translations. The structure and function of the visual cortex has inspired many models for invariant object recognition. In this paper, we propose a hierarchical model for object recognition based on the two well-known properties of the visual cortex neurons:(More)