To enable real-time perception of surroundings, an environment recognition and path planning system uses depth cameras to process RGB-D data, classifying terrain types such as flat surfaces, slopes, stairs, obstacles, and uneven ground. Integrated obstacle detection and mapping ensure safe navigation by preventing collisions and optimizing foothold selection. Additionally, path planning algorithms generate adaptive trajectories based on environmental constraints, allowing efficient movement through complex terrains. This framework enhances situational awareness and enables autonomous decision-making for seamless and safe locomotion.

To enhance remote monitoring, real-time control, and adaptive updates, EXO Lab is integrating a cloud-based system with the Application Module (AM). This connection enables data upload, optimized control strategies, and seamless software updates. A user-friendly interface allows operators to monitor system states, adjust control parameters, and visualize motion analytics. Remote access supports personalized tuning based on user needs and environments. This cloudintegrated framework, powered by AM, ensures continuous learning, improved usability, and adaptive exoskeleton control.