Mobile　robotic　arms　require　the　cooperation　of　a　mobile　platform　and　a　robotic　arm　to　reach　the　desired　position　rapidly　and　efficiently　to　complete　the　specified　operations.　By　improving　the　estimation　function　of　the　A∗algorithm,　the　number　of　turns　in　the　path　can　be　reduced,　making　the　overall　movement　of　the　robot　smoother　and　more　efficient.　For　the　path　planning　of　the　robotic　arm,　a　fast　random　tree　method　is　introduced,　and　the　gravity　component　is　added　to　guide　the　growth　direction　of　the　random　tree　for　problems　such　as　poor　real-time　performance　and　non-global　optimal　results.　For　the　issue　of　oscillations　and　sudden　changes　in　the　planning　results,　a　smoothing　process　is　applied　to　the　paths　obtained　by　the　improved　algorithm.　Simulation　results　and　experiments　show　that　the　improved　path　planning　method　has　better　performance　in　the　application　of　mobile　robotic　arm.　©　2021　ACM.