The recent developments in the field of UAV and robotic path planning highlight a significant shift towards more sophisticated, multi-objective optimization algorithms that incorporate kinematic constraints, dynamic feasibility, and collision avoidance. Innovations in this area are increasingly focusing on the integration of whole-body motion planning for aerial manipulators, the development of benchmarks for heterogeneous multi-UAV systems, and the application of novel algorithms for fast-revisit coverage path planning. These advancements are not only enhancing the efficiency and safety of UAV operations but are also paving the way for more complex tasks such as cooperative inspection and emergency rescue missions.

Noteworthy papers include:

• The introduction of the NMOPSO algorithm, which outperforms existing multi-objective and metaheuristic optimization algorithms in UAV path planning.
• The development of a whole-body integrated motion planning framework for aerial manipulators, marking a significant step forward in tackling complex manipulation tasks.
• The proposal of the CARIC benchmark, which has become a valuable tool for evaluating motion planning algorithms in heterogeneous multi-UAV systems.
• The FaRe-CPP algorithm, which significantly reduces revisit times and path lengths in coverage path planning for autonomous mobile patrol robots.
• The APF-SA algorithm, which demonstrates robust path planning capabilities for UAVs in complex 3D environments with obstacles and no-fly zones.
• The application of the teaching-learning-based optimization algorithm for UAV swarm path planning, ensuring desired formation and safe operation.