To ensure reliable and scalable communication among various modules in the proposed platform, a customized application-level communication protocol is developed on top of the FD-CAN layer. The system employs two independent FD-CAN channels, each configured in standard identifier mode (11-bit) and operated at a data rate of 5 Mbps using Bit Rate Switching (BRS) for enhanced throughput. Automatic retransmission and transmit pause features are enabled to improve communication reliability under time-critical control conditions.

To support modular and extensible communication, the 11-bit standard identifier is structured into three subfields: message type, source node ID, and target node ID. The message type, occupying the upper three bits of the identifier, defines the functional category of the data being transmitted. This message type is categorized into four classes: emergency (EMCY), synchronization (SYNC), Service Data Object (SDO), and Process Data Object (PDO).

This proposed communication protocol provides platform-level scalability, as new devices can be integrated by assigning respective node IDs without modifying the protocol structure. Message priority is inherently managed through the identifier field, allowing critical messages to be transmitted with higher arbitration precedence. This flexible and modular design supports seamless expansion and reliable coordination across distributed modules.

Since a wearable robot is an integrated system of both robot and human, gravity has a substantial impact on overall system performance and stability. Under gravitational loading, the robot must exert additional force to counteract the wearer’s body weight, which can lead to inefficiency, fatigue, and instability. EXO-Lab implements precise gravity compensation for the robot system or the human–robot integrated system to support smoother and more energy-efficient assistance. For effective gravity compensation, the center of mass (CoM) should be estimated accurately. Considering performance and computational capacity, EXO-Lab models the robot body and the human body for precise CoM estimation and gravity compensation.

Previously, wearable robots relied on crutches to maintain balance due to the difficulty of stabilizing the system. Recent advancements, however, have enabled wearable robots to maintain balance independently without crutches. EXO-Lab conducts research and development to support independent balance maintenance by utilizing embedded ground reaction force sensors and estimated whole-body state information. As the control module (CM) plays a role analogous to the cerebellum in human motion architecture, CM supports balancing by calculating joint-level trajectories that match the real-time center of mass (CoM) and center of pressure (CoP).