This article presents a comprehensive review of control algorithms used in mobile robotics, a field in constant evolution. Mobile robotics has seen significant advances in recent years, driven by the demand for applications in various sectors, such as industrial automation, space exploration, and medical care. The review focuses on control algorithms that address specific challenges in navigation, localization, mapping, and path planning in changing and unknown environments. Classical approaches, such as PID control and methods based on classical control theory, as well as modern techniques, including deep learning and model-based planning, are discussed in detail. In addition, practical applications and remaining challenges in implementing these algorithms in real-world mobile robots are highlighted. Ultimately, this review provides a comprehensive overview of the diversity and complexity of control algorithms in mobile robotics, helping researchers and practitioners to better understand the options available to address specific problems in this exciting area of study.

翻译：本文全面综述了移动机器人领域中不断演进的控制算法。近年来，受工业自动化、太空探索和医疗护理等多领域应用需求的驱动，移动机器人技术取得了显著进展。本综述聚焦于在变化和未知环境中解决导航、定位、建图及路径规划等特定挑战的控制算法。详细讨论了经典方法（如PID控制及基于经典控制理论的方法）与现代技术（包括深度学习和基于模型的规划）。此外，还重点阐述了这些算法在实际移动机器人中应用时的实践案例与剩余挑战。最终，本文全面呈现了移动机器人控制算法的多样性与复杂性，有助于研究人员和从业者更好地理解解决该激动人心研究领域中具体问题时可用的选择方案。