Objective To propose a point and line (PL)-simultaneous localization and mapping (SLAM) algorithm and to compare it with oriented FAST and rotated BRIEF (ORB)-SLAM2, so as to improve the global localization accuracy and real-time performance of SLAM algorithm for medical service robots. Methods The PL-SLAM algorithm added line features based on point feature in the process of feature extraction, and carried out mapping and global localization in the complex medical environment according to the point and line features after fusion. The public datasets (EuRoc and KITTI) were used to compare the PL-SLAM and ORB-SLAM2 algorithms, and the comprehensive performance of autonomous navigation of the medical service robots was tested. Results Compared with the ORB-SLAM2 algorithm, PL-SLAM algorithm extracted more point and line features in weak texture scenario, and effectively enhanced the global localization accuracy and real-time performance. The rotation error of the PL-SLAM algorithm decreased by 42.2% and the runtime increased by 55.9%. Conclusion PL-SLAM algorithm can effectively improve global localization accuracy and the real-time performance of medical service robots.