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Autonomous Biped Navigation Through Cluttered 3D Environments

We developed a navigation system that allows humanoids to autonomously navigate in previously unknown, cluttered environments. Our approach relies on data from consumer-grade depth cameras such as an ASUS Xtion or Microsoft Kinect. From the depth data, our system estimates the robot's pose and maintains a heightmap representation of the environment. Based on this model, our technique iteratively computes sequences of safe actions including footsteps and whole-body motions, leading the robot to target locations. Hereby, the planner chooses from a set of actions that consists of planar footsteps, step-over actions, as well as parameterized step-onto and step-down actions. To efficiently check for collisions during planning, we developed a new approach that takes into account the shape of the robot and the obstacles.

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The video below shows our Nao humanoid equipped with an ASUS Xtion Pro Live on top of its head navigating in a cluttered environments. The robot is able to traverse highly challenging passages by building an accurate heightmap from the data of the onboard depth camera and choosing suitable actions.

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