Obstacle detection is one of the major focus area on image processing. For mobile robots, obstacle detection and collision avoidance is a notorious problem and is still a part of the modern research. There are already a lot of research have been done so far for obstacle detection and collision avoidance. This thesis evaluates the existing various well-known methods and sensors for collision free navigation of the mobile robot. For moving obstacle detection purpose the frame difference approach is adopted. Robotino® is used as the mobile robot platform and additionally Microsoft Kinect is used as 3D sensor. For getting information from the environment about obstacle, the 9-built-in distance sensor of Robotino® and 3D depth image data from the Kinect is used. The combination is done to get the maximum advantages for obstacles information. The detection of moving object in front of the sensor is a major interest of this work.

Obstacle detection is one of the major focus area on image processing. For mobile robots, obstacle detection and collision avoidance is a notorious problem and is still a part of the modern research. There are already a lot of research have been done so far for obstacle detection and collision avoidance. This thesis evaluates the existing various well-known methods and sensors for collision free navigation of the mobile robot. For moving obstacle detection purpose the frame difference approach is adopted. Robotino® is used as the mobile robot platform and additionally Microsoft Kinect is used as 3D sensor. For getting information from the environment about obstacle, the 9-built-in distance sensor of Robotino® and 3D depth image data from the Kinect is used. The combination is done to get the maximum advantages for obstacles information. The detection of moving object in front of the sensor is a major interest of this work.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-08-16T20:26:43Z No. of bitstreams: 1 OtoEmersonDeAlbuquerque_DISSERT.pdf: 17507163 bytes, checksum: 867588f4230e7727922cb32ba8c2b9d5 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-08-18T22:15:11Z (GMT) No. of bitstreams: 1 OtoEmersonDeAlbuquerque_DISSERT.pdf: 17507163 bytes, checksum: 867588f4230e7727922cb32ba8c2b9d5 (MD5) / Made available in DSpace on 2016-08-18T22:15:11Z (GMT). No. of bitstreams: 1 OtoEmersonDeAlbuquerque_DISSERT.pdf: 17507163 bytes, checksum: 867588f4230e7727922cb32ba8c2b9d5 (MD5) Previous issue date: 2016-04-27 / Ag?ncia Nacional do Petr?leo - ANP / Esse trabalho tem como objetivo o estudo de t?cnicas de vis?o computacional para o reconhecimento de gestos humanos, bem como sua aplica??o ao controle de rob?s m?veis. S?o analisados os desafios e propostas algumas solu??es para o desenvolvimento de uma interface simples, a qual permita o reconhecimento e a interpreta??o dos gestos gerados pela m?o humana, no intuito de controlar os movimentos de um rob?. Neste contexto, foi desenvolvido um programa em C++ para captar as imagens geradas por uma c?mera de alta defini??o e, a partir da informa??o extra?da das imagens, definir qual movimento seria realizado pelo rob?. Para auxiliar a tarefa de reconhecimento e processamento da imagem captada foram utilizadas fun??es da biblioteca OpenCV. Os resultados obtidos com a interface desenvolvida confirmam e demonstram a viabilidade de aplica??o desta tecnologia. / The main objective of this work was to enable the recognition of human gestures through the development of a computer program. The program created captures the gestures executed by the user through a camera attached to the computer and sends it to the robot command referring to the gesture. They were interpreted in total ve gestures made by human hand. The software (developed in C ++) widely used the computer vision concepts and open source library OpenCV that directly impact the overall e ciency of the control of mobile robots. The computer vision concepts take into account the use of lters to smooth/blur the image noise reduction, color space to better suit the developer's desktop as well as useful information for manipulating digital images. The OpenCV library was essential in creating the project because it was possible to use various functions/procedures for complete control lters, image borders, image area, the geometric center of borders, exchange of color spaces, convex hull and convexity defect, plus all the necessary means for the characterization of imaged features. During the development of the software was the appearance of several problems, as false positives (noise), underperforming the insertion of various lters with sizes oversized masks, as well as problems arising from the choice of color space for processing human skin tones. However, after the development of seven versions of the control software, it was possible to minimize the occurrence of false positives due to a better use of lters combined with a well-dimensioned mask size (tested at run time) all associated with a programming logic that has been perfected over the construction of the seven versions. After all the development is managed software that met the established requirements. After the completion of the control software, it was observed that the overall e ectiveness of the various programs, highlighting in particular the V programs: 84.75 %, with VI: 93.00 % and VII with: 94.67 % showed that the nal program performed well in interpreting gestures, proving that it was possible the mobile robot control through human gestures without the need for external accessories to give it a better mobility and cost savings for maintain such a system. The great merit of the program was to assist capacity in demystifying the man set/machine therefore uses an easy and intuitive interface for control of mobile robots. Another important feature observed is that to control the mobile robot is not necessary to be close to the same, as to control the equipment is necessary to receive only the address that the Robotino passes to the program via network or Wi-Fi.