An intelligent, predictive control approach to the high-speed cross-country autonomous navigation problem
Real-Time Correlation-Based Stereo Vision with Reduced Border Errors
International Journal of Computer Vision
Improving traversability of quadruped walking robots using body movement in 3D rough terrains
Robotics and Autonomous Systems
Stereo-vision-based navigation of a six-legged walking robot in unknown rough terrain
International Journal of Robotics Research
Velocity selection for high-speed UGVs in rough unknown terrains using force prediction
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
Shock Reduction for Autonomous Navigation on Rough Terrain: A Difference of Normals Approach
Proceedings of Conference on Advances In Robotics
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A navigation algorithm for mobile robots in unknown rough terrain has been developed. The algorithm is solely based on stereo images and suitable for wheeled and legged robots. The navigation system is able to guide the robot along a short and safe path to a goal specified by the operator and given in coordinates relative to the starting point of the robot. The algorithm uses visual odometry for localization. The terrain is modeled from stereo images and its traversability is estimated. A D* Lite planner is used for efficiently planning a short and safe path by incorporating terrain traversability in the planning process. The robot actively explores its environment as it follows the path to the goal. The algorithm has been tested on a wheel driven mobile robot and on a six-legged walking robot on rough terrain.