Unmanned　Aerial　Vehicle　(UAV)　are　increasingly　utilized　in　power　line　inspection　work,　the　3D　path　planning　for　UAV　urgently　needs　to　be　addressed.　Artificial　Fish　Swarm　Algorithm　(AFSA)　is　one　of　the　most　common　used　methods　for　the　3D　path　planning　of　UAVs,　but　the　problems　of　rapid　convergence　and　susceptibility　to　less　optimal　solutions　for　AFSA　needs　to　be　solved.　For　this　reason,　a　3D　path　planning　method　for　power　inspection　UAVs　based　on　an　Improved　Artificial　Fish　Swarm　Algorithm　(IAFSA)　is　proposed　in　this　paper.　This　algorithm　references　the　metropolis　criterion　of　the　Simulated　Annealing　(SA)　algorithm　and　introduces　an　anti-Metropolis　criterion　to　escape　from　less　optimal　solutions.　Firstly,　a　3D　mountainous　terrain　model　is　constructed　based　on　the　environment　where　power　inspection　UAV　perform　inspection　tasks　in　mountainous　areas.　Then,　the　anti-Metropolis　criterion　is　introduced　into　AFSA　to　escape　from　less　optimal　solutions.　Finally,　to　satisfy　the　performance　constraints　of　the　UAV,　a　cubic　spline　interpolation　function　is　used　to　smooth　the　path.　Comparative　simulation　experiments　with　Particle　Swarm　Optimization　(PSO),　SA,　and　AFSA　are　carried　out.　The　result　shows　that　IAFSA　proposed　in　this　paper　not　only　exhibits　superior　optimization　performance　in　different　terrain　environments,　but　also　maintains　the　rapid　convergence　and　optimization　accuracy　of　AFSA.　©　Beijing　Paike　Culture　Commu.　Co.,　Ltd.　2025.