This　paper　proposes　a　method　combining　binocular　vision　and　deep　learning　to　identify　and　locate　ripe　tomatoes　in　greenhouses.　First,　the　CBAM　attention　mechanism　module　is　added　to　the　YOLO　V3　model　to　improve　the　robustness　of　the　YOLO　V3　model　to　the　greenhouse　environment,　and　then　the　tomato　results　identified　by　the　improved　YOLOV3　CBAM　are　fused　with　the　three-dimensional　information　obtained　by　the　binocular　stereo　camera.　to　obtain　the　threedimensional　position　information　of　the　tomato　fruit.　After　testing,　the　model　has　an　accuracy　of　89.15%　for　tomato　recognition,　the　AP　is　86.17%,　and　the　F1　value　is　82%.　The　relative　error　of　the　tomato　fruit　positioning　is　less　than　1.5%.　Finally,　the　model　was　arranged　in　the　greenhouse　to　test　the　tomato　picking　robot,　which　verifies　the　practicability　of　the　method.　©　2023　SPIE.　All　rights　reserved.