Path Planning for UAVs Under Communication Constraints Using SPLAT! and MILP

Abstract

We will in this paper address the problem of offline path planning for Unmanned Aerial Vehicles (UAVs). Our goal is to find paths that meet mission objectives, are safe with respect to collision and grounding, fuel efficient and satisfy criteria for communication. Due to the many nonconvex constraints of the problem, Mixed Integer Linear Programming (MILP) will be used in finding the path. Approximate communication constraints and terrain avoidance constraints are used in the MILP formulation. To achieve more accurate prediction of the ability to communicate, the path is then analyzed in the radio propagation toolbox SPLAT!, and if the UAVs are not able to communicate according to design criteria for bandwidth, constraints are modified in the optimization problem in an iterative manner. The approach is exemplified with the following setup: The path of two UAVs are planned so they can serve as relay nodes between a target without line of sight to the base station.

Motion- and Communication-Planning of Unmanned Aerial Vehicles in Delay Tolerant Network using Mixed-Integer Linear Programming

“…In Grøtli and Johansen (2012b) we dealt with motion planning in order to create a relay chain between two stationary ground-or surface nodes. In comparison, in this paper we have presented a solution to a surveillance mission planning problem.…”

“…We approximate V pi in a similar manner as in Chaudhry et al (2004), here in the three-dimensional case as in Grøtli and Johansen (2012b), by introducing the constraints:…”

“…Trajectory generation for autonomous vehicles was considered in Schouwenaars et al (2001), while a robotic ball game was the application of Earl and D'Andrea (2002). Since then MILP has been used extensively for path planning problems, in particular for UAVs, both for single and multi-vehicle systems, see Richards and How (2002), Ma and Miller (2006), Shengxiang and Hailong (2008), Kuwata and How (2011), Grøtli and Johansen (2012b) and Grøtli and Johansen (2012c). In Schouwenaars et al (2006) connectivity constrained trajectory planning for autonomous helicopters through cluttered environments was studied.…”

“…In on of our previous papers, Grøtli and Johansen (2012b), we described how paths for multiple UAVs can be planned to create a communication chain between two base stations, also known as chaining, Dixon and Frew (2007). In Grøtli and Johansen (2012c) paths were planned for a multi-task mission similar to that presented in this paper, and where the mission objective only could be met if one of the vehicles were used as a relay node.…”

“…As in Grøtli and Johansen (2012b) and Grøtli and Johansen (2012c) we analyze the planned paths in a radio propagation simulator to get a more accurate prediction of the radio path loss between the vehicles, and between the vehicles and the base station. In the MILP formulation the ability to communicate at a certain data rate depends on the distance between the nodes.…”