The field of autonomous navigation and mapping is moving towards more dynamic and adaptive approaches, integrating real-time sensor data with prior knowledge to improve safety and efficiency. Researchers are exploring new methods to fuse data from various sources, such as LiDAR and Building Information Modeling (BIM), to create more accurate and up-to-date maps of environments. This is particularly important in applications such as construction robotics, where navigation safety is critical. Noteworthy papers in this area include:

• BIM-Discrepancy-Driven Active Sensing for Risk-Aware UAV-UGV Navigation, which presents a framework for cooperative navigation between UAVs and UGVs that reduces navigation risk by 58%.
• Perception-aware Exploration for Consumer-grade UAVs, which extends state-of-the-art autonomous exploration to consumer-level UAVs, enabling safe and efficient mapping with limited hardware.