This work presents an egocentric vision module for adaptive gait planning in lower-limb exoskeletons. By combining exoskeleton-mounted and head-mounted cameras, the system builds a unified 3D map of the environment, enabling early obstacle detection and robust terrain classification. An Environment-Adaptive Gait Planning (EAGP) system computes safe footpaths, while augmented reality feedback provides intuitive visualization for the user. A dedicated dataset with step and corridor walking scenarios was collected to support development and evaluation.