For the robot navigation system used in an unpredictable environment, it is effective to create a path that robots can track to reach a destination. When we think about autonomous construction of navigation path using potential field, the created potential field can be very noisy with many local peak due to the unsynchronized update by robots. In this research, we propose a hill climbing algorithm that can track these dynamic noisy potential field using minimization of information entropy. Also, we will show the effectiveness of proposed algorithm by tracking different types of noisy potential fields.
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