Terrain Dependant Control of Hexapod Robots Using Vision
The ability to traverse uneven terrain is one of the key advantages of legged robots. However, their effectiveness relies on selecting appropriate gait parameters, such as stride height and leg stiffness. The optimal parameters highly depend on the characteristics of the terrain. This work presents a novel stereo vision based terrain sensing method for a hexapod robot with 30 degrees of freedom. The terrain in front of the robot is analyzed by extracting a set of features which enable the system to characterize a large number of terrain types. Gait parameters and leg stiffness for impedance control are adapted based on this terrain characterization. Experiments show that adaptive impedance control leads to efficient locomotion in terms of energy consumption, mission success and body stability.
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