Route planning with ordered constraints

Route planning in realistic terrains is a critical task for many autonomous agents such as mobile robots, autonomous vehicles or Computer Generated Forces. The route planning problem is often formulated as one of finding a minimum-cost route between two locations in a digitised map which represents a complex terrain of variable altitude, where the cost of a route is an indication of its quality. However route planners which attempt to optimise a single measure of plan quality often fail to provide real-time performance and the composite cost functions on which they are based are difficult to devise or justify. In this paper, we present a new approach to route planning in complex terrains based on a novel constraintbased search procedure, A with bounded costs (ABC), which generalises the single criterion optimisation problem solved by conventional route planners. Rather than attempting to find the lowest cost plan to achieve a goal, we plan to satisfy an ordered set constraints where the position of the constraint in the ordering reflects its importance. This approach provides a means of more clearly specifying agent tasks and more precisely evaluating the resulting plans.