From PID to swarms: A decade of advancements in drone control and path planning - A systematic review (2013–2023)

Abstract

This systematic literature review synthesizes and evaluates existing research on drone control and path planning, encompassing the principles of swarm intelligence and nature-inspired algorithms. However, it is not limited to these; it also explores other algorithms to provide a comprehensive overview of the state-of-the-art in this rapidly evolving field. The review identifies and analyzes key trends, challenges, and advancements in drone control and path planning. It investigates the evolution of control strategies, ranging from classical proportional-integral-derivative (PID) controllers to modern swarm algorithms and reinforcement learning-based techniques. Additionally, it explores path planning methodologies, including traditional optimization algorithms and heuristic-based approaches, and specifically, swarm algorithms within the context of drone swarms. The emphasis on nature-inspired intelligent computation extends to the exploration of swarm intelligence and cooperative planning as integral components of drone path planning. By synthesizing and critically analyzing the literature, this systematic review not only presents a comprehensive understanding of the current landscape of drone control and path planning, but it also acknowledges the role of various nature-inspired algorithms, including but not limited to swarm intelligence, and identifies avenues for future research in this evolving field.