With no GPS and no map, a robot can still find its own position and build a map of its surroundings from camera images alone. From feature tracking through epipolar geometry, the difference between Visual Odometry and SLAM, the lineage of landmark algorithms from ORB-SLAM to LSD-SLAM and DSO, and Bundle Adjustment, a systematic ground-up tour of how Visual-SLAM actually works.
September 6, 2026 Robotics PrimerA camera is strong on meaning, a LiDAR is strong on geometry, an IMU is strong on motion — and each has its own blind spot. From the probabilistic and optimization-based math that fuses them (Kalman Filters, Factor Graphs) to concrete pairings like VIO (Camera×IMU), LIO (LiDAR×IMU), and BEV Fusion (Camera×LiDAR), a systematic tour of how Sensor Fusion turns several sensors into a single world model.
September 5, 2026 Robotics PrimerObject Detection draws boxes around things; Semantic Segmentation colors in every pixel by meaning. From the difference between the two, through Instance and Panoptic Segmentation, the lineage from R-CNN to YOLO, DETR and DINO, all the way to their 3D point-cloud counterparts — a systematic tour of the fundamentals of scene understanding.