ITC/USA 2009 Conference Proceedings / The Forty-Fifth Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2009 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Several navigation technologies exist, which can facilitate the generation of Time Space Positioning Information (TSPI) in urban environments. These include GPS, image-based localization, radio-based localization and dead reckoning. This paper first presents a basic overview of these techniques including advantages and limitations of each. We present an approach to localization in urban environments, based on environment learning and collaborative navigation using multiple homogeneous and non-homogeneous localization technologies, fused to form a multi-sensor system.

This thesis focuses on which kinds of aspects that would be extra important when two or more persons are collaboratively navigating a single character in a game world. With help of interaction design methods during this process, such as literature researches and usability tests, a low-fidelity and a mid-fidelity prototype were created to find these aspects. In the tests, I also used a high-fidelity game to compare my prototypes with. The conclusion and discussion in this thesis presents different sorts of new ideas and possibilities concerning the different aspects that could lead to developing new interesting games with collaborative navigation.

Made available in DSpace on 2014-12-17T14:55:48Z (GMT). No. of bitstreams: 1 MarceloBN.pdf: 1368278 bytes, checksum: e9f6ea9d9353cb33144a3fc036bd57dc (MD5) Previous issue date: 2005-12-20 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / This work proposes a method to localize a simple humanoid robot, without embedded sensors, using images taken from an extern camera and image processing techniques. Once the robot is localized relative to the camera, supposing we know the position of the camera relative to the world, we can compute the position of the robot relative to the world. To make the camera move in the work space, we will use another mobile robot with wheels, which has a precise locating system, and will place the camera on it. Once the humanoid is localized in the work space, we can take the necessary actions to move it. Simultaneously, we will move the camera robot, so it will take good images of the humanoid. The mainly contributions of this work are: the idea of using another mobile robot to aid the navigation of a humanoid robot without and advanced embedded electronics; chosing of the intrinsic and extrinsic calibration methods appropriated to the task, especially in the real time part; and the collaborative algorithm of simultaneous navigation of the robots / Este trabalho prop?e um m?todo para localizar um rob? human?ide simples, sem sensores embarcados, utilizando imagens obtidas por uma c?mera externa e t?cnicas de processamento de imagens. Localizando o rob? em rela??o ? c?mera, e supondo conhecida a posi??o da c?mera em rela??o ao mundo, podemos determinar a posi??o do rob? human?ide em rela??o ao mundo. Para que a posi??o da c?mera n?o seja fixa, utilizamos um outro rob? m?vel com rodas, dotado de um sistema de localiza??o preciso, sobre o qual ser? colocada a c?mera. Uma vez que o human?ide seja localizado no ambiente de trabalho, podemos tomar as a??es necess?rias para realizar a sua movimenta??o. Simultaneamente, movimentamos o rob? que cont?m a c?mera, de forma que este tenha uma boa visada do human?ide. As principais contribui??es deste trabalho s?o: a id?ia de utilizar um segundo rob? m?vel para auxiliar a movimenta??o de um rob? human?ide sem eletr?nica embarcada avan?ada; a escolha de m?todos de calibra??o dos par?metros intr?nsecos e extr?nsecos da c?mera apropriados para a aplica??o em quest?o, especialmente na parte em tempo real; e o algoritmo colaborativo de movimenta??o simult?nea dos dois rob?s