Wednesday, August 28, 2013

3-D mapping in real time, without the drift

New technique creates highly detailed, accurate 3-D maps in real time.

Article from MITnews

Computer scientists at MIT and the National University of Ireland (NUI) at Maynooth have developed a mapping algorithm that creates dense, highly detailed 3-D maps of indoor and outdoor environments in real time.
The researchers tested their algorithm on videos taken with a low-cost Kinect camera, including one that explores the serpentine halls and stairways of MIT’s Stata Center. Applying their mapping technique to these videos, the researchers created rich, three-dimensional maps as the camera explored its surroundings.
As the camera circled back to its starting point, the researchers found that after returning to a location recognized as familiar, the algorithm was able to quickly stitch images together to effectively “close the loop,” creating a continuous, realistic 3-D map in real time.
The technique solves a major problem in the robotic mapping community that’s known as either “loop closure” or “drift”: As a camera pans across a room or travels down a corridor, it invariably introduces slight errors in the estimated path taken. A doorway may shift a bit to the right, or a wall may appear slightly taller than it is. Over relatively long distances, these errors can compound, resulting in a disjointed map, with walls and stairways that don’t exactly line up.
In contrast, the new mapping technique determines how to connect a map by tracking a camera’s pose, or position in space, throughout its route. When a camera returns to a place where it’s already been, the algorithm determines which points within the 3-D map to adjust, based on the camera’s previous poses.
“Before the map has been corrected, it’s sort of all tangled up in itself,” says Thomas Whelan, a PhD student at NUI. “We use knowledge of where the camera’s been to untangle it. The technique we developed allows you to shift the map, so it warps and bends into place.”
The technique, he says, may be used to guide robots through potentially hazardous or unknown environments. Whelan’s colleague John Leonard, a professor of mechanical engineering at MIT, also envisions a more benign application.
“I have this dream of making a complete model of all of MIT,” says Leonard, who is also affiliated with MIT’s Computer Science and Artificial Intelligence Laboratory.  “With this 3-D map, a potential applicant for the freshman class could sort of ‘swim’ through MIT like it’s a big aquarium. There’s still more work to do, but I think it’s doable.”
Leonard, Whelan and the other members of the team — Michael Kaess of MIT and John McDonald of NUI — will present their work at the 2013 International Conference on Intelligent Robots and Systems in Tokyo.

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