Vector Field Histogram - VFH

VFH

The Vector Field Histogram was developed with the aim to be computationally efficient, robust, and insensitive to misreadings. In practice, the VFH algorithm has proven to be fast and reliable, especially when traversing densely populated obstacle courses.

At the center of the VFH algorithm is the use of statistical representation of obstacles, through histogram grids (see also occupancy grid). Such representation is well suited for inaccurate sensor data, and gives the potential for the fusion of multiple sensor readings.

The VFH algorithm contains three major components:

1. Cartesian histogram grid: a two-dimensional Cartesian histogram grid is constructed with the robot's range sensors, such as a sonar or a laser rangefinder. The grid is continuously updated in real time.
2. Polar histogram: a one-dimensional polar histogram is constructed by reducing the Cartesian histogram around the momentary location of the robot.
3. Candidate valley: consecutive sectors with a polar obstacle density below threshold, known as candidate valleys, is selected based on the proximity to the target direction.

Once the direction of the center of the selected candidate direction is determined, orientation of the robot is steered to match. The speed of the robot is reduced when approaching the obstacles head-on.