The recent developments in the research area of autonomous and electric vehicles, unmanned aerial vehicles (UAVs), and advanced air mobility (AAM) have shown significant advancements in energy efficiency, control systems, and operational capabilities. The field is moving towards more integrated and adaptive control strategies, leveraging model predictive control (MPC) frameworks to optimize performance under various conditions. Innovations in power and thermal management for electric vehicles, particularly in connected and automated scenarios, are enhancing battery life and overall system efficiency. UAVs are seeing improvements in landing control, especially in adverse conditions, with novel approaches to handle ship oscillations and wind disturbances. Additionally, the integration of hybrid power systems in aircraft designs is being explored to enhance versatility and safety. Notably, there is a growing focus on energy-efficient trajectory planning for autonomous electric vehicles, which not only optimizes energy use but also integrates seamlessly with existing driving algorithms. The use of hardware-in-the-loop (HWIL) systems for state estimation in micro-aerial vehicles is another promising area, aiming to enable fully autonomous control in complex environments. Furthermore, the development of buoyant aerial robotic platforms for extraterrestrial exploration, such as Venus, marks a significant milestone in aerobot technology. Overall, the field is advancing towards more robust, efficient, and autonomous systems, with a strong emphasis on real-world applicability and performance optimization.

Noteworthy papers include one proposing an integrated power and thermal management strategy for CAEVs, which significantly reduces battery degradation and improves energy efficiency. Another notable paper presents a novel approach to UAV landing control on moving ships, enhancing yaw authority and demonstrating successful landings in adverse conditions. Lastly, a paper on energy-efficient hybrid model predictive trajectory planning for autonomous electric vehicles showcases substantial improvements in energy recovery and tracking performance.