[Paper Reading] MAVIS: Multi-Camera Augmented Visual-Inertial SLAM using SE2(3) Based Exact IMU Pre-integration
多相机系统的好处是，更大的FOV，对环境的全向观测，提高定位精度和弱纹理场景下的鲁棒性。 坏处则是更多的传感器带来了更多的计算消耗。The proper handling of measurements from all cameras is crucial for balancing accuracy, robustness, and computational efficiency.
[14] extended ORB-SLAM2 [15] to multi-camera setups, supporting various rigidly coupled multi-camera systems. [16] introduced an adaptive SLAM system design for arbitrary multi-camera setups, requiring no sensorspecific tuning. Several works [17]–[21] focus on utilizing a surround-view camera system, often with multiple nonoverlapping monocular cameras, or specializing in motion estimation for ground vehicles. While demonstrating advantages in robustness in complex environments, these methods exhibit limited performance in highly dynamic scenarios and minor accuracy improvements in real-world experiments.
Inspired by [22] and [9], we employ a localization strategy based on a local map, utilizing 2D extracted features and local 3D map points for precise pose estimation