Pedestrian　simulation　modeling　has　become　an　important　means　to　study　the　dynamic　characters　of　dense　populations.　In　the　continuous　pedestrian　simulation　model　for　complex　simulation　scenario　with　obstacles,　the　pedestrian　path　planning　algorithm　is　an　indispensable　component,　which　is　used　for　the　calculation　of　pedestrian　macro　path　and　microscopic　movement　desired　direction.　However,　there　is　less　efficiency　and　poor　robustness　in　the　existing　pedestrian　path　planning　algorithm.　To　address　this　issue,　we　propose　a　new　pedestrian　path　planning　algorithm　to　solve　these　problems　in　this　article.　In　our　algorithm,　we　have　two　steps　to　determine　pedestrian　movement　path,　that　is,　the　discrete　potential　fields　are　first　generated　by　the　flood　fill　algorithm　and　then　the　pedestrian　desired　speeds　are　determined　along　the　negative　gradient　direction　in　the　discrete　potential　field.　Combined　with　the　social　force　model,　the　proposed　algorithm　is　applied　in　a　corridor,　a　simple　scene,　and　a　complex　scene,　respectively,　to　verify　its　effectiveness　and　efficiency.　The　results　demonstrate　that　the　proposed　pedestrian　path　planning　algorithm　in　this　article　can　greatly　improve　the　computational　efficiency　of　the　continuous　pedestrian　simulation　model,　strengthen　the　robustness　of　application　in　complex　scenes.