Jmvega guide robot

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  • Project Name: Navigation and autolocation over a guide robot
  • Authors: Julio Vega Pérez (jm [dot] vegap [at] alumnos [dot] urjc [dot] es) and Jose María Cañas Plaza (jmplaza [at] gsyc [dot] es)
  • Academic Year: 2007-2008
  • Degree: Grad
  • Tags: robot, guide, location, navigation
  • Technology: c, c++, jde suite, openGL
  • State: Finished
  • Abstract:

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.


  • Documentation: 
Master Thesis: PDF (latex code)
Presentation: PDF (OpenOffice code)


  • Presentation:



  • Videos:


Contents

Local navigation on Pioneer Robot using GPP

This method uses a navigation function to generate a gradient field that represents the optimal (lowest-cost) path to the goal at every point in the workspace. Additionally, we've developed an integrated sensor fusion system that allows incremental construction of an unknown or uncertain environment, for local navigation.


Local navigation on Pioneer Robot using VFF

In this video, we can see a real-time obstacle avoidance method entitled Virtual Forces Field. It permits the detection of unknown obstacles simultaneously with the steering of the mobile robot to avoid collisions and advancing toward the target. The novelty of this approach lies in the integration of two known concepts: Certainty Grids for obstacle representation, and Potential Fields for navigation.


Global navigation using GPP

In this video, we can see a simulation on navigation using Gradient Path Planning Algorithm. Under OpenGL we have improved the agility of response to graphical level.


Localization using MonteCarlo Method

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.


Other applications using OpenGL

Now, we can see a new application entitled "Jde productions". We've tried to see a film in the Laboratory's ceiling designed using OpenGL. The result is a new virtual world where we can navigate for watching films!

  • More information:
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