The Effect of Transparency on Human-Exoskeleton Interaction

The exoskeleton robot is a new type of cooperative robot that forms a typical human-robot system with its wearer. In order to achieve a common task goal, human-exoskeleton cooperative tasks need to integrate natural cooperation. Exoskeleton robots must not only predict the task goals of human partners but also make human partners anticipate their own intentions and perceive the execution of tasks during cooperation. Therefore, studying the transparency of exoskeleton robots plays a very important role in improving the mutual understanding between humans and exoskeletons and enhancing the interoperability and naturalness of human-robot cooperation. In previous studies, we investigated the human-exoskeleton behavioral information transfer path given the lack of an efficient communication mechanism between the wearer and the exoskeleton named AIDER. A tactile feedback method based on the change of vibration intensity was proposed to transmit the current walking state of the human-exoskeleton system to the wearer, and a voice-based interaction method was proposed to express the human-robot behavioral intention. To verify the effectiveness of the above methods, this study analyzed the wearer's mental workload using functional near-infrared spectroscopy while performing the human-exoskeleton walking tasks in the different modes. The results showed that the mental load of the transparency mode (TM) was similar to that of the normal walking mode (NWM). However, the data fluctuated more than in the other two modes in the NTM (non-transparency mode), indicating that the mental workload is heavier than in the other groups. Therefore, transparency can help reduce the mental workload of the wearer. It was shown that transparency plays an important role in the collaboration between humans and robots, which can improve efficiency and trust between the exoskeleton and the wearer.