An important application of mobile robots is to perform tasks in environments which are dangerous for humans. For example, robots should explore the surface of other planets, climb into caves or provide information from disaster sites. These application areas are usually unstructured and have challenging terrain. Thus, there are several challenges for a mobile robot to autonomously navigate in such environments: Wheels or legs can slip, lighting conditions can be difficult due to strong shadows, and the definition of what is an obstacle and what can be traversed depends on the capabilities of the robot.


Our rough terrain navigation method overcomes these challenges. The robot keeps track of its current pose by fusing measurements from an inertial measurement unit (IMU) with stereo visual odometry and, if available, leg odometry measurements. Hence, its pose estimate is robust against slip and bad visual conditions.


Using the pose estimate, a 2.5D digital elevation map of the environment is created from stereo vision using SGM. The terrain roughness, slopes and step heights are calculated and evaluated according to the motion capabilities of the robot. The result is a cost map giving the traversability of each terrain patch.

Based on the cost map, safe and short paths to given goal points are planned and efficiently replanned using D* Lite when new information is available. Thus, the robot is able to autonomously navigate to goal coordinates in unknown rough terrain.





Annett Stelzer, Heiko Hirschmüller, Martin Görner: Stereo-Vision-Based Navigation of a Six-Legged Walking Robot in Unknown Rough Terrain, The International Journal of Robotics Research, Special Issue on Robot Vision, Volume 31, Issue 4, 2012, pp. 381-402 [Download]

 Annett Chilian, Heiko Hirschmüller, Martin Görner: Multisensor Data Fusion for Robust Pose Estimation of a Six-Legged Walking Robot, IEEE International Conference on Intelligent Robots and Systems (IROS), Sept. 25-30, 2011, San Francisco, CA, USA.

Martin Görner, Annett Chilian, Heiko Hirschmüller: Towards an Autonomous Walking Robot for Planetary Surfaces. I-SAIRAS 2010, Aug. 29 - Sept. 1, 2010, Sapporo, Japan.

Annett Chilian, Heiko Hirschmüller: Stereo Camera Based Navigation of Mobile Robots on Rough Terrain. IEEE International Conference on Intelligent Robots and Systems (IROS), Oct. 11-15, 2009, St. Louis, USA.



Annett Stelzer

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