The　problem　of　path　planning　in　the　field　of　robot　navigation　is　now　a　major　research　hot　spot.　On　the　premise　of　ensuring　that　the　robot　can　successfully　navigate　to　the　target　point,　the　safety　of　the　path　also　needs　to　be　considered.　In　order　to　find　a　safer　path,　a　safe　pathfinding　path　planning　method　is　proposed,　which　introduces　two　safety　parameters　that　affect　the　path　selection:　hazard　coefficient　and　movement　coefficient.　After　defining　two　security　parameters,　design　an　appropriate　reward　function　and　use　A2C　algorithm　and　PPO　algorithm　to　guide　the　robot　to　conduct　reinforcement　learning.　The　experiment　will　be　conducted　on　a　two-dimensional　grid　map　containing　various　obstacles.　By　conducting　comparative　experiments,　it　is　verified　that　the　safety　pathfinding　method　proposed　in　this　paper　is　feasible　and　reasonable,　and　can　enable　the　robot　to　choose　a　safer　road　instead　of　a　faster　road　when　planning　the　path.