Sixth　generation　(6G)　wireless　networks　require　very　low　latency　and　an　ultra-high　data　rate,　which　have　become　the　main　challenges　for　future　wireless　communications.　To　effectively　balance　the　requirements　of　6G　and　the　extreme　shortage　of　capacity　within　the　existing　wireless　networks,　sensing-assisted　communications　in　the　terahertz　(THz)　band　with　unmanned　aerial　vehicles　(UAVs)　is　proposed.　In　this　scenario,　the　THz-UAV　acts　as　an　aerial　base　station　to　provide　information　on　users　and　sensing　signals　and　detect　the　THz　channel　to　assist　UAV　communication.　However,　communication　and　sensing　signals　that　use　the　same　resources　can　cause　interference　with　each　other.　Therefore,　we　research　a　cooperative　method　of　co-existence　between　sensing　and　communication　signals　in　the　same　frequency　and　time　allocation　to　reduce　the　interference.　We　then　formulate　an　optimization　problem　to　minimize　the　total　delay　by　jointly　optimizing　the　UAV　trajectory,　frequency　association,　and　transmission　power　of　each　user.　The　resulting　problem　is　a　non-convex　and　mixed　integer　optimization　problem,　which　is　challenging　to　solve.　By　resorting　to　the　Lagrange　multiplier　and　proximal　policy　optimization　(PPO)　method,　we　propose　an　overall　alternating　optimization　algorithm　to　solve　this　problem　in　an　iterative　way.　Specifically,　given　the　UAV　location　and　frequency,　the　sub-problem　of　the　sensing　and　communication　transmission　powers　is　transformed　into　a　convex　problem,　which　is　solved　by　the　Lagrange　multiplier　method.　Second,　in　each　iteration,　for　given　sensing　and　communication　transmission　powers,　we　relax　the　discrete　variable　to　a　continuous　variable　and　use　the　PPO　algorithm　to　tackle　the　sub-problem　of　joint　optimization　of　the　UAV　location　and　frequency.　The　results　show　that　the　proposed　algorithm　reduces　the　delay　and　improves　the　transmission　rate　when　compared　with　the　conventional　greedy　algorithm.