Research and Analysis of Robot SLAM Technology in Complex Scenarios

With the advancement of robotics technology, robots are being deployed in application scenarios. They are no longer confined to basic indoor environments but have extended to outdoor environments. Therefore, the demand for reliable SLAM technology is increasing. This article examines three challenging scenarios: texture loss in low-light images, high dynamic interference, and signal degradation in steep terrain. First, the paper analyzes the reasons why the SLAM system is prone to failure under these conditions. For each scenario, two solutions are proposed. Through method comparison and analysis, we put forward improvement suggestions to break through technical bottlenecks, such as enhancing feature extraction ability through computation, integrating point and line features to achieve trajectory tracking, processing moving objects using semantic information, and fusing data from multiple sensors. By conducting a comparative analysis of three scenarios, the study identified three common challenges: insufficient environmental adaptability of the SLAM system, inadequate handling capacity for moving objects, and efficiency bottlenecks. Finally, three research directions were proposed: Firstly, SLAM should shift from constructing static maps to understanding dynamic scene changes; Secondly, more efficient methods need to be developed to adapt to various types of devices and environments; Finally, the system should possess the ability to continuously learn from new environments.