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Humanoid Robot Navigation in Complex Indoor Environments

Humanoid Robot Navigation in Complex Indoor Environments. Maren Bennewitz Humanoid Robots Lab. Joint work with Armin Hornung, Johannes Garimort, Attila Görög, Daniel Maier, Stefan Osswald, Kai Wurm, Cyrill Stachniss, and Wolfram Burgard. Motivation & Objective.

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Humanoid Robot Navigation in Complex Indoor Environments

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  1. Humanoid Robot Navigationin Complex Indoor Environments Maren Bennewitz Humanoid Robots Lab Joint work with Armin Hornung, Johannes Garimort, Attila Görög, Daniel Maier, Stefan Osswald, Kai Wurm, Cyrill Stachniss, and Wolfram Burgard

  2. Motivation & Objective • Humanoid robots bridge the gab between human and robot navigation • Humanoid robot navigation in complex indoor environments • Considering objects important for human navigation

  3. Goals • Robust techniques for • 3D environment modeling • Localization • Navigation and action planning • Challenges arise from • Inherently noisy sensor data • Inaccurate motion execution • Huge state space • Dynamics

  4. 3D World Representation • Based on octrees • Probabilistic representation of occupancy including unknown • Multi-resolution: Resolution can be changed efficiently • Memory efficient • Open sourcehttp://octomap.sf.net

  5. 3D World Model • Freiburg computer science campus (292 x 167 x 28 m³, 20 cm resolution)

  6. Accurate 6D Localization Monte Carlo localization using the 3D world model Estimation of the 6D pose 3D coordinate of the torso Roll, pitch, and yaw angles Integrated information Estimated body movement Sensor data: 2D laser range scanner, IMU, and joint encoders

  7. Accurate 6D Localization

  8. Humanoid Navigation • Given the world model and the localization, the robot can navigate in the environment

  9. Online Traversability Estimation • Given sparse 3D laser data • Learn classifiers (color+texture) to detect obstacles in images

  10. Use the Traversability Estimate for Path Planning

  11. Footstep Planning • Avoid obstacles by stepping over them • Heuristic search given set of footsteps

  12. Efficient Replanning • Plans may become invalid due to changes in the environment • Replanning with D* Lite [Koenig & Likhachev, AAAI 2000] • Extended to continuous footstep locations

  13. Open Problems • Classification of regions according to navigation complexity

  14. Open Problems • Classification of regions according to navigation complexity • Efficient updating of 3D map structures • Representing (movable) objects in space • Representing typical configurations of objects in 3D (e.g., doors, drawers)

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