JDERobot » navigation http://blog.jderobot.org Just another WordPress weblog Fri, 23 Jul 2010 14:13:55 +0000 http://wordpress.org/?v=2.8.6 en hourly 1 Finished Guide Robot Project http://blog.jderobot.org/?p=31 http://blog.jderobot.org/?p=31#comments Mon, 22 Sep 2008 10:14:59 +0000 Julio Vega http://blog.jde.gsyc.es/?p=31 I’ve finished my project. Our approach specifically addresses issues such as safe navigation in unmodified and dynamic environments, like Departamental II of this university. We’ve solved the following problems:

- Navigation in dynamic environments. Public places are often packed with people. People behave not necessarily cooperatively. Our approach provides means for safe and effective navigation through crowds.

- Navigation in unmodified environments. No modification of the environment is necessary for the robot’s operation.

- Localization. In every operation, our robot continuously tracks its position using its maps. Position estimates are necessary for the robot to know where to move when navigating to a specific goal, and to ensure the robot does not accidentally leave its operational area.

To navigate reliably in indoor environments, a mobile robot must know where it is. Thus, reliable position estimation is a key problem in mobile robotics. We believe that probabilistic approaches are among the most promising candidates to providing a comprehensive and real-time solution to the robot localization problem.

So, in this video we’ve used Monte Carlo localization method where we represent the probability density involved by maintaining a set of samples that are randomly drawn from it. We show experimentally that the resulting method is able to efficiently localize a mobile robot without knowledge of its starting location.

Link for more information: http://jde.gsyc.es/index.php/jmvega_guide_robot

]]> http://blog.jderobot.org/?feed=rss2&p=31 0 Navigation Simulation over OpenGL http://blog.jderobot.org/?p=5 http://blog.jderobot.org/?p=5#comments Tue, 01 Jul 2008 09:09:02 +0000 Julio Vega http://blog.jde.gsyc.es/?p=5 In this video, we can see a navigation simulation using Gradient Path Planning Algorithm. Under OpenGL we have improved the agility of response to graphical level. We’re design our virtual department; the blue mark represent the virtual robot, and the red mark is the goal (office 113).

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