In farming operations, one of the fundamental issues facing a farmer is the cost of running the
farm. If the equipment the farmer is using can be made more efficient, the cost of farming will be
reduced. One way of making agricultural equipment more efficient is to develop automated or
autonomous functions for the equipment. One of the fundamental tasks for autonomous
equipment is to plan the path for the equipment to travel. This paper reports the research on the
feasibility of creating an automated method of path planning for autonomous agricultural
equipment. Genetic algorithms were chosen to plan the paths with a primary goal of creating an
optimal path guiding the equipment to completely cover a field while avoiding all known
obstacles. Two example fields were designed for evaluating the feasibility of this concept on
simple problems. While simulation results verified the feasibility of this conceptual path
planning method, they also indicated that further development would be required before the
algorithm could actually be implemented on agricultural equipment for real-world field
applications.