The Potential Field Approach (PFA) [1] is a well known method in reactive robot navigation. The basic idea simply models (detected) obstacles as repulsors and goal(s) as attractor(s) depending on their proximity to the robot. The rotational of the resulting field returns the motion vectors for our mobile. PFA are intuitive, simple, smooth and, up to a point, reliable.

Despite being relatively old, this technique is still widely used in navigation. Indeed, many robotic wheelchairs use PFA to avoid collisions by removing control from the user when there is present danger in what we call "safeguard operation mode". Still, PFA per se can not be used for much more in its original formulation due to well reported problems: i) oscillations in corridor-like situations; ii) sensitivity to local minima; and iii) local traps. The following viewo shows the commented problems:

These problems can be solved by more powerful, enhanced versions of PFA, mostly based on making them less reactive. Algorithms used in assistive navigation instead of PFA include the Dynamic Window Approach and the Vector Field Histogram (VFH).


[1] Khatib, O., "Real-Time Obstacle Avoidance for Manipulators and Mobile Robots", Int. J. of Robotic Research, Vol.5, No.1 (1986), p.60