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.
- Integrated Perception, Mapping, and Footstep Planning for
Humanoid Navigation Among 3D Obstacles.
D. Maier, C. Lutz, and M. Bennewitz.
In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013.
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.
Direct link to YouTube