A　kinematic　information　acquisition　system　of　human　lower　limbs　based　on　attitude　and　heading　reference　system　(AHRS)　was　developed　for　a　lower　limb　soft　assistance　robot.　The　AHRS　of　the　system　has　the　characteristics　of　small　volume　and　low　power　consumption,　and　can　be　worn　for　a　long　time　and　easy　to　keep　a　tight　connection　with　human　body　through　the　bind.　The　design　of　AHRS　integrates　Kalman　filter　(KF)　intend　to　improve　the　accuracy　of　the　data,　multi-channel　data　communication　and　transmission　to　PC　through　the　wireless　network　formed　by　ZigBee.　Then,　the　kinematic　model　of　the　human　lower　limbs　was　established,　and　the　conversion　relationship　between　the　AHRS　measurement　angle　and　the　human　lower　limb　posture　angle　was　introduced.　At　the　same　time,　considering　the　robot　provides　different　forces　under　the　different　gait　activities,　the　decision　tree　classifier　for　classification　that　can　identify　different　gait　activities　and　assist　robots　provide　power　to　human　effectively　was　designed.　In　a　variety　of　gait　activities,　making　data　collected　by　this　system　to　compare　with　data　from　the　Vicon　system　shows　that　the　data　of　the　system　has　high　precision,　and　also　verifies　that　the　system　has　good　stability　and　reliability.　Additionally,　a　large　number　of　gait　data　were　used　to　train　decision　tree　classifier　and　the　accuracy　of　gait　recognition　is　verified　by　the　classification　experiment　of　unknow　gait　activities.　©　2023　Beijing　University　of　Technology.　All　rights　reserved.