Aiming　at　the　problem　of　limited　energy　stored　in　unmanned　aerial　vehicle　(UAV),　a　resource　allocation　strategy　for　UAV-assisted　edge　computing　in　wireless　powered　communication　networks　is　investigated　in　this　paper.　By　deploying　a　laser　beam　director　on　the　ground,　sufficient　energy　can　be　provided　for　the　UAV　in　a　short　period　of　time.　Then,　multiple　ground　terminals　obtain　energy　from　this　UAV　by　radio　frequency　energy　harvesting　method　and　offload　their　computational　tasks　to　the　UAV　with　edge　server.　The　resource　allocation　problem　is　modeled　as　an　optimization　problem.　The　optimization　objective　is　to　minimize　the　total　energy　consumption　of　the　UAV　subject　to　the　constraints　of　energy　and　data　causality,　computational　resources,　and　transmitting　power.　The　suboptimal　solution　is　obtained　by　introducing　an　imperialist　competitive　algorithm.　Simulation　results　show　that　the　imperialist　competitive　algorithm　consumes　less　energy　compared　with　the　particle　swarm　optimization　algorithm　and　the　equal　upload　time　allocation　method.