Adaptive Foothold Selection for a Hexapod Robot Walking on Rough Terrain
نویسنده
چکیده
This paper introduces an adaptive foothold selection algorithm for a legged robot walking on a rough terrain. The proposed algorithm searches for the best footholds to prevent slippages. It uses a known grid map of the surrounding terrain and a polynomial-based approximation method to create a decision surface. The robot learns from experiments, therefore no a priori expert’s knowledge is required. The results of simulations show that the method is general enough to work properly on various types of terrain. These results have been also verified on the real walking robot ’Ragno’.
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