In complex warehouse and logistics scenarios， accurate perception of robot position and attitude is essential to guarantee efficient and safe operation. In order to achieve the above purpose， a logistics robot localization algorithm based on binocular vision simultaneous localization and mapping （SLAM） multi-dimensional data fusion is proposed. Combined with the binocular vision SLAM algorithm， the multi-dimensional fusion of sensor monitoring data is completed， and then the map model of the robot motion scene is created. In this model， the trajectory of the logistics robot is estimated， and the function expression of the target algorithm is solved through the extraction and matching operation of the position and pose point features so as to realize the logistics robot positioning based on the binocular vision SLAM multi-dimensional data fusion. Experimental results demonstrate that the proposed algorithm effectively reduces position deviation between the robot''s real-time position and preset trajectory. The trajectory generated by pose points excludes obstacle points， enabling the robot to operate efficiently in complex logistics environments.