Controlling the Distance Between the Robot and Target During the Tracking Process

The tracking process of dynamic target has been played a significant role in industrial environment especially in military industrial, medical and surgical applications, dinger seeking and automatic control cars.In this paper implemented mobile robot and visionary system with two parts the first one is 3D Camera ( Kinect ) fixed on the mobile robot with computer connection . the kinect Camera installation on computer have been install series of open source software respectively . This work involves constructing integrated in MATLAB program automatically. It depends on a new approach in analyzing the robotic environment by a Kinect. The approach uses colors to detect and recognize the locations object and target.By analysis and processing the image captured by 3D Camera (Kinect) in computer are detection the target in the image, find it's center and measure the depth from robot to target .The calculated depth and angle from image processing in computer is transmitting from computer to robot by using wireless unit and finally the robot go to this location. Finally by using specific algorithm can be controlling the distance between robot and target.The second part of visionary system is a WebCamera fixed in the roof of the working environment to detect the target and robot. The instantaneous distance between robot and target in each frame is finding by WebCam. Keywords: Mobile Robot, Object Tracking, Visionary System, 3D Kinec

Improvement of Auto-Tracking Mobile Robot based on HSI Color Model

Auto tracking mobile robot is a device that able to detect and track a target. For an auto tracking device, the most crucial part of the system is the object identification and tracking of the moving targets. In order to improve the accuracy of identification of object in different illumination and background conditions, the implementation of HSI color model is used in image processing algorithm. In this project HSI-based color enhancement algorithm were used for object identification. This is because HSI parameter are more stable in different light and background conditions, so it is selected as the main parameters of this system. Pixy CMUcam5 is used as the vision sensor while Arduino Uno as the main microcontroller that controls all the input and output of the device. Moreover, two servo motors were used to control the pan-tilt movement of the vision sensor. Experimental results demonstrate that when HSI color-based filtering algorithm is applied to visual tracking it improves the accuracy and stability of tracking under the condition of varying brightness, or even in the low-light-level environment. Besides that, this algorithm also prevents tracking loss due to object color appears in the background

An intelligent multi-floor mobile robot transportation system in life science laboratories

In this dissertation, a new intelligent multi-floor transportation system based on mobile robot is presented to connect the distributed laboratories in multi-floor environment. In the system, new indoor mapping and localization are presented, hybrid path planning is proposed, and an automated doors management system is presented. In addition, a hybrid strategy with innovative floor estimation to handle the elevator operations is implemented. Finally the presented system controls the working processes of the related sub-system. The experiments prove the efficiency of the presented system