This paper presents a road-network search route planning algorithm by which multiple autonomous vehicles are able to efficiently visit every road identified in the map in the context of the Chinese postman problem. Since the typical Chinese postman algorithm can be applied solely to a connected road-network in which ground vehicles are involved, it is modified to be used for a general type of roadmap including unconnected roads as well as the operational and physical constraints of UAVs. For this, a multi-choice multi-dimensional Knapsack problem is formulated to find an optimal solution minimising a flight time and then solved via mixed integer linear programming. To deal with the dynamic constraints of the UAVs, the Dubins theory is used for path generation. In particular, a circular-circular-circular type of the Dubins path is exploited based on a differential geometry to guarantee that the vehicles follow the road precisely in a densely distributed road environment. Moreover, to overcome the computational burden of the multi-choice multi-dimensional Knapsack algorithm, a nearest insertion and auction based approximation algorithm is newly introduced. The properties and performance of the proposed algorithm are evaluated via numerical simulations operating on a real village map and randomly generated maps with different parameters.
Oh et al. REF used a drone to examine the road network search problem in the Dubins path case when a group of unconnected roads need to be searched.
Coordinated road-network search route planning by a team of UAVs
Int. J. Systems Science
Int. J. Systems Science
Mathematics Computer Science