A new real-time obstacle avoidance method for mobile robots has been developed and implemented. This method, named the vector field histogram (VFH), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward the target. The VFH method uses a two-dimensional Cartesian histogram grid as a world model. This world model is updated continuously with range data sampled by on-board range sensors. The VFH method subsequently employs a two-stage data-reduction process in order to compute the desired control commands for the vehicle. In the first stage the histogram grid is reduced to a onedimensional polar histogram that is constructed around the robot's momentary location. Each sector in the polar histogram contains a value representing the polar obstacle density in that direction. In the second stage, the algorithm selects the most suitable sector from among all polar histogram sectors with a low polar obstacle density, and the steering of the robot is aligned with that direction. Experimental results from a mobile robot traversing densely cluttered obstacle courses in smooth and continuous motion and at an average speed of 0.6 0.7m/sec demonstrate the power of the VFH method.
Regarding to obstacle avoidance systems, a very first approach that has been employed in robotics since the early nineties is the Vector Field Histogram (VFH) REF .
THE VECTOR FIELD HISTOGRAM-FAST OBSTACLE AVOIDANCE FOR MOBILE ROBOTS
ICRA
Computer Science Mathematics