Vector Field Histogram Method

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Obstacle avoidance is a key component in any mobile robotic system. If we want our system to move about in the real world we have to consider that there are obstacles not represented in any a priori map. The obstacles can either be static as for example a table or dynamic as a human or another robot. What we think of by obstacle avoidance is the ability to go from one place to another without running into things on the way. This means that obstacle avoidance is tightly coupled with path planning, it is not exactly the same thing but they depend on each other so much that they often are indistinguishable. In general, there are two kinds of methods for obstacle avoidance path planning, global and local. These build on the same ideas as the architectures mentioned earlier, a global obstacle avoidance algorithm requires a relative complete…show more content…
The Vector Field Histogram Method
After identifying the problems with potential field methods, Koren and Borenstein continued their work by proposing a method that deals with the shortcomings of potential fields. In [6] they suggest a method for fast obstacle avoidance that they call the Vector Field Histogram (VFH). The method will only briefly be discussed here since it is not immediately related to the algorithm studied in this thesis. It is, however, an important method for obstacle avoidance and therefore worth mentioning.
The VFH method uses the histogram grid described above to represent the environment in which the robot travels. This makes the map fairly accurate even when the robot is equipped with sonars. The contents of each cell in the histogram grid is treated as an obstacle vector, the direction of the vector is the direction from the current position of the robot to the obstacle. The magnitude of the vector is given by a formula that considers both the certainty value of the cell and the distance to the cell (note that with a certainty value of zero the magnitude of the obstacle vector will also be
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