Modular self-reconfigurable robotic systems are designed to adapt their shape by rearranging their components, offering versatility, robustness, and cost-effectiveness. These systems consist of modular building blocks with uniform interfaces, enabling them to perform various tasks and recover from damage. The field has evolved from proof-of-concept systems to complex implementations and simulations over the past two decades. Modular robots can be classified into architectures such as lattice, chain/tree, and mobile, each with distinct characteristics and applications. Key challenges include hardware design, planning and control algorithms, and application-specific requirements. Hardware challenges involve optimizing module design for strength, precision, and efficiency. Planning and control algorithms must handle large-scale systems, including parallel motion, reconfiguration, and obstacle navigation. Application challenges include identifying specific use cases where these systems can demonstrate their benefits. Examples of self-reconfigurable systems include PolyBot G3, the Programmable Parts, Molecubes, SuperBot, and Miche. These systems showcase various capabilities, such as self-assembly, self-repair, and self-replication. Despite progress, challenges remain in scaling up systems, achieving robustness, and reducing costs. Future goals include creating large-scale systems, self-repairing robots, self-sustaining systems, and self-replicating robots. These systems have potential applications in space exploration, disaster response, and other areas requiring adaptability and resilience. The research community continues to explore new algorithms, hardware, and applications to advance the field of modular self-reconfigurable robotics.Modular self-reconfigurable robotic systems are designed to adapt their shape by rearranging their components, offering versatility, robustness, and cost-effectiveness. These systems consist of modular building blocks with uniform interfaces, enabling them to perform various tasks and recover from damage. The field has evolved from proof-of-concept systems to complex implementations and simulations over the past two decades. Modular robots can be classified into architectures such as lattice, chain/tree, and mobile, each with distinct characteristics and applications. Key challenges include hardware design, planning and control algorithms, and application-specific requirements. Hardware challenges involve optimizing module design for strength, precision, and efficiency. Planning and control algorithms must handle large-scale systems, including parallel motion, reconfiguration, and obstacle navigation. Application challenges include identifying specific use cases where these systems can demonstrate their benefits. Examples of self-reconfigurable systems include PolyBot G3, the Programmable Parts, Molecubes, SuperBot, and Miche. These systems showcase various capabilities, such as self-assembly, self-repair, and self-replication. Despite progress, challenges remain in scaling up systems, achieving robustness, and reducing costs. Future goals include creating large-scale systems, self-repairing robots, self-sustaining systems, and self-replicating robots. These systems have potential applications in space exploration, disaster response, and other areas requiring adaptability and resilience. The research community continues to explore new algorithms, hardware, and applications to advance the field of modular self-reconfigurable robotics.