Converted this previously Octopress-generated site to Pelican. Boy, that was painful!
Time for another post. This one shows the Selective Bathymetric SLAM approach, detailed in this recent paper, Navigational Error Reduction of Autonomous Underwater Vehicles with Selective Bathymetric SLAM.
I thought I should post something on an area I've been working in more recently, so here is my simulation of the Simultaneous Localisation and Mapping (SLAM) technique, as applied to an autonomous vehicle navigating through waypoints across a feature-rich terrain.
I dug up some more old VRML simulation replays created some time ago. These ones demonstrate the dynamic response of CH-47B Chinook and UH-1H helicopters with externally slung loads undergoing a either simple disturbance or manoeuvre. The coupled-body dynamic simulation was performed in Matlab and then exported to VRML for visualisation.
Now that the multiprocessing library comes standard in Python 2.6, I thought I'd migrate some of my apps to take full advantage. However, there aren't many examples out there showing how to write a basic multiprocessing program with a graphical front-end. In order to prototype the program design, I wrote a simple wxPython script.
Just tidied up my VRMLtrace python program. This script converts any simulation/pose data (position+orientation) into a VRML model for visualisation. It uses a template file, a VRML model of the vehicle and a data file to generate the VRML.
This is a VRML simulation replay which demonstrates the dynamic response of a CH-47B Chinook helicopter with an externally slung Medium Maintenance Shelter (MMS) load undergoing a simple manoeuvre.