This paper represents a method for mobile robot navigation in environments where obstacles are partially unknown. The method uses a path selection mechanism that creates innovative paths through the unknown environment and learns to use routes that are more reliable. This approach is implemented on Khepera robot and verified against shortest path following by wave transform algorithms. Based on the experimental data, we claim that robot's trajectory planned by wave transform algorithms is difficult to predict and control unless the environment is completely modelled and the localisation errors are small. We show that even small unmodelled obstacles can cause large deviation from the preplanned path. Our complementary approach of path selection decreases the risk of path following and increases the predictability of robot's behaviour.
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