This article reviews recent progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial, ground, and underwater vehicles, has been a key research area. Recent results are categorized into consensus, formation control, optimization, task assignment, and estimation. A discussion section summarizes existing research and proposes future directions and open problems. The article begins with an introduction to control theory, highlighting its development from the early 20th century to modern applications. It discusses the difference between centralized and distributed control approaches, emphasizing the latter due to physical constraints. Distributed control aims to achieve cooperative group performance with low cost, high robustness, and adaptability. The study of distributed control was initially inspired by distributed computing, management science, and statistical physics. Pioneering works in control systems include studies on asynchronous agreement and consensus algorithms under various information constraints. Several journal special issues and reviews have been published since 2006, covering consensus, formation control, optimization, task assignment, and estimation. The article reviews recent research in consensus, formation control, optimization, task assignment, and estimation. Consensus involves agents reaching agreement through local interactions. Formation control aims to coordinate agents into a desired geometric configuration. Optimization focuses on algorithmic developments for large-scale systems. Task assignment involves distributing tasks based on local information. Estimation and control use local estimation of global information. The article introduces graph theory and stochastic matrices, essential for analyzing network topologies. It discusses consensus under deterministic and stochastic network topologies, highlighting the role of stochastic matrices in convergence analysis. Complex dynamical systems, including nonlinear oscillators, complex networks, and nonholonomic robots, are also analyzed. Delay effects, sampled-data frameworks, quantization, asynchronous effects, convergence speed, and finite-time convergence are considered. The study of consensus with complex systems focuses on analyzing stability and convergence under various dynamics. Delay effects are analyzed, with time delay affecting system performance and stability. Sampled-data frameworks are used to model systems with discrete-time updates. Quantization introduces digital constraints, affecting consensus performance. Asynchronous effects are studied, with agents updating independently. Convergence speed and finite-time convergence are important performance measures for consensus algorithms. The article concludes by emphasizing the importance of considering multiple physical properties and control performance in consensus research. Formation control is highlighted as a practical application requiring coordinated geometric structures. The study of formation control is presented in the next section.This article reviews recent progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial, ground, and underwater vehicles, has been a key research area. Recent results are categorized into consensus, formation control, optimization, task assignment, and estimation. A discussion section summarizes existing research and proposes future directions and open problems. The article begins with an introduction to control theory, highlighting its development from the early 20th century to modern applications. It discusses the difference between centralized and distributed control approaches, emphasizing the latter due to physical constraints. Distributed control aims to achieve cooperative group performance with low cost, high robustness, and adaptability. The study of distributed control was initially inspired by distributed computing, management science, and statistical physics. Pioneering works in control systems include studies on asynchronous agreement and consensus algorithms under various information constraints. Several journal special issues and reviews have been published since 2006, covering consensus, formation control, optimization, task assignment, and estimation. The article reviews recent research in consensus, formation control, optimization, task assignment, and estimation. Consensus involves agents reaching agreement through local interactions. Formation control aims to coordinate agents into a desired geometric configuration. Optimization focuses on algorithmic developments for large-scale systems. Task assignment involves distributing tasks based on local information. Estimation and control use local estimation of global information. The article introduces graph theory and stochastic matrices, essential for analyzing network topologies. It discusses consensus under deterministic and stochastic network topologies, highlighting the role of stochastic matrices in convergence analysis. Complex dynamical systems, including nonlinear oscillators, complex networks, and nonholonomic robots, are also analyzed. Delay effects, sampled-data frameworks, quantization, asynchronous effects, convergence speed, and finite-time convergence are considered. The study of consensus with complex systems focuses on analyzing stability and convergence under various dynamics. Delay effects are analyzed, with time delay affecting system performance and stability. Sampled-data frameworks are used to model systems with discrete-time updates. Quantization introduces digital constraints, affecting consensus performance. Asynchronous effects are studied, with agents updating independently. Convergence speed and finite-time convergence are important performance measures for consensus algorithms. The article concludes by emphasizing the importance of considering multiple physical properties and control performance in consensus research. Formation control is highlighted as a practical application requiring coordinated geometric structures. The study of formation control is presented in the next section.