Camera, LiDAR, and IMU Spatiotemporal Calibration: Methodological Review and Research Perspectives

Abstract

Multi-sensor fusion systems involving Light Detection and Ranging (LiDAR), cameras, and inertial measurement units (IMUs) have been widely adopted in fields such as autonomous driving and robotics due to their complementary perception capabilities. This widespread application has led to a growing demand for accurate sensor calibration. Although numerous calibration methods have been proposed in recent years for various sensor combinations, such as camera–IMU, LiDAR–IMU, camera–LiDAR, and camera–LiDAR–IMU, there remains a lack of systematic reviews and comparative analyses of these approaches. This paper focuses on extrinsic calibration techniques for LiDAR, cameras, and IMU, providing a comprehensive review of the latest developments across the four types of sensor combinations. We further analyze the strengths and limitations of existing methods, summarize the evaluation criteria for calibration, and outline potential future research directions for the benefit of the academic community.