The field of autonomous navigation and path planning is witnessing significant advancements, driven by the development of innovative algorithms and techniques. A key trend is the integration of multiple modalities and sensors to enhance navigation efficiency and adaptability in complex environments. Researchers are also focusing on improving the energy efficiency of autonomous systems, particularly in outdoor environments where terrain variations affect energy consumption. Furthermore, there is a growing interest in developing path planning methods that can handle dynamic obstacles and uneven terrains, enabling autonomous systems to operate effectively in real-world scenarios. Noteworthy papers in this area include the proposal of a distributed gradient-based deployment strategy for hybrid wireless sensor networks, which maximizes coverage while adapting to regional importance. Another significant contribution is the development of an adaptive coverage control approach for multiple autonomous off-road vehicles in dynamic agricultural fields, which integrates Unmanned Aerial Vehicles for obstacle detection and terrain assessment. Additionally, the introduction of FMTx, an extension of the Fast Marching Tree algorithm, enables efficient and consistent replanning in dynamic environments, making it a valuable tool for real-time robotic navigation.