Bridge cracks are a critical factor affecting the operational performance of bridges, and crack detection is crucial for bridge maintenance. Traditional methods and data processing for bridge crack detection are primarily based on manual operations, resulting in low detection efficiency, accuracy, and a strong subjective element. In recent years, numerous scholars have developed innovative bridge crack detection devices to address these issues. Examples include climbing robots equipped with high-definition cameras, wheel-type eddy current adsorption robots, and underwater robots, all used for data collection. Simultaneously, the development of efficient and accurate crack detection algorithms forms the foundation of crack detection. Balancing detection speed and accuracy remains a focal point of research for many scholars. This paper provides a comprehensive review of recent developments in bridge crack detection devices and data processing methods.