The field of autonomous navigation and control is moving towards more robust and efficient methods for navigating complex environments. Recent developments have focused on integrating perception and control systems to enable real-time navigation and tracking. There is a growing trend towards using model predictive control and sliding mode control to stabilize periodic trajectories and improve robustness to disturbances. Additionally, researchers are exploring the use of optical navigation and station-keeping pipelines for precise control of spacecraft and robots. Noteworthy papers include: A paper that presents a real-time autonomous track navigation framework for nonholonomic differential-drive mobile robots, which jointly integrates multi-task visual perception and a provably stable tracking controller. A paper that proposes a combined sliding-mode control and subspace stabilization methodology for orbital stabilization of periodic trajectories in underactuated mechanical systems.