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Autonomously Climbing Complex Staircases and Traversing Ramps

We developed an approach to enable a humanoid robot to autonomously climb up complex staircases. We first reconstruct a 3D model of the staircase based on laser range data acquired with a humanoid. The robot then globally estimates its pose in the 3D model, which is subsequently refined by integrating visual observations. We use the 3D staircase model and the estimated pose to project edges corresponding to stair contours into monocular camera images. By detecting edges in the images and associating them to projected model edges, the robot is able to accurately locate itself towards the stairs and to climb them reliably. Furthermore, we developed methods that enable a humanoid robot to traverse ramps using only vision and inertial data for sensing. The robot locates the beginning of the ramp using visual observations, walks down with regular corrections based on the inertial data, and finally determines the end of the ramp by detecting the ending edge before exiting the ramp.


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Videos:

The first two videos below show how the Nao acquires an accurate 3D model of the staircase and then autonomously climbs it up to the top. As can be seen, the robot moves its head to observe stair edges in camera images and accurately positions itself for climbing the next step. The last video shows the humanoid traversing a ramp using only vision and inertial data for sensing.

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