Autonomous　robotic　massage　holds　the　potential　to　alleviate　the　workload　of　nurses　and　improve　the　quality　of　healthcare.　However,　the　complexity　of　the　task　and　the　dynamic　of　the　environment　present　significant　challenges　for　robotic　massage.　This　paper　presents　a　vision-based　robotic　massage　(VBRM)　framework　that　facilitates　autonomous　robot　massaging　of　the　human　body　while　ensuring　safe　operation　in　a　dynamic　environment.　The　VBRM　framework　allows　the　operator　to　define　the　massage　trajectory　by　drawing　a　2D　curve　on　an　RGB　image.　An　interactive　trajectory　planning　method　is　developed　to　calculate　a　3D　massage　trajectory　from　the　2D　trajectory.　This　method　accounts　for　potential　movements　of　the　human　body　and　updates　the　planned　trajectory　using　rigid　point　cloud　registration.　Additionally,　a　hybrid　motion/force　controller　is　employed　to　regulate　the　motion　of　the　robot’s　end-effector,　considering　the　possibility　of　excessive　contact　force.　The　proposed　framework　enables　the　operator　to　adjust　the　massage　trajectory　and　speed　according　to　their　requirements.　Real-world　experiments　are　conducted　to　evaluate　the　efficacy　of　the　proposed　approach.　The　results　demonstrate　that　the　framework　enables　successful　planning　and　execution　of　the　massage　task　in　a　dynamic　environment.　Furthermore,　the　operator　has　the　flexibility　to　set　the　massage　trajectory,　speed,　and　contact　force　arbitrarily,　thereby　enhancing　human–machine　interaction.　©　The　Author(s)　2024.