The field of robot navigation and control is rapidly advancing, with a focus on developing innovative methods for motion planning and control in complex environments. Researchers are exploring new approaches to overcome the limitations of traditional methods, such as the use of model predictive control, fuzzy logic, and hybrid actuation mechanisms. These advances are enabling robots to navigate and interact with their environments in more sophisticated ways, including the ability to switch between different modes of locomotion, such as driving and flying, and to adapt to changing environmental conditions. Noteworthy papers in this area include:

• DRPA-MPPI, which introduces a dynamic repulsive potential augmented MPPI for reactive navigation in unstructured environments, and
• Decremental Dynamics Planning, which integrates dynamic constraints into the entire planning process for improved robot navigation performance.