To　deal　with　the　problem　of　stable　walking　of　quadruped　robots　on　slopes,　a　gait　planning　algorithm　framework　for　quadruped　robots　facing　unknown　slopes　is　proposed.　We　estimated　the　terrain　slope　by　the　attitude　information　measured　by　the　inertial　measurement　unit　(IMU)　without　relying　on　the　robot　vision.　The　crawl　gait　was　adopted,　and　the　center　of　gravity　trajectory　planning　was　carried　out　based　on　the　stability　criterion　zero-moment　point　(ZMP).　Then,　the　augmented　random　search　(ARS)　algorithm　was　used　to　modulate　the　parameters　of　the　Bezier　curve　to　realize　the　planning　of　the　robot　foot　trajectory.　Additionally,　the　robot　can　adjust　the　posture　in　real　time　to　follow　the　desired　joint　angle,　which　realizes　the　adaptive　adjustment　of　the　robot＇s　posture　during　the　slope　movement.　Simulation　experiment　results　show　that　the　proposed　algorithm　for　slope　gait　planning　can　adaptively　adjust　the　robot＇s　attitude　and　stably　pass　through　the　slope　environment　when　the　slope　is　unknown.