Virtual Obstacle Avoidance Strategy: Navigating through a Complex Environment While Interacting with Virtual and...

Area of Science:

• Robotics
• Human-Computer Interaction
• Rehabilitation Engineering

Background:

• Robotic walking devices are crucial for intensive gait rehabilitation.
• Mixed Reality (MR) can enhance engagement in therapeutic exercises.
• Shared control strategies are needed for intuitive human-robot interaction in mobility aids.

Purpose of the Study:

• To introduce an MR-based multimodal human-robot interaction strategy for a Smart Walker.
• To enhance safe navigation and intuitive mobility training through personalized virtual scenarios.
• To evaluate the effectiveness and self-explanatory nature of the MR interface.

Main Methods:

• Development of an MR system integrating virtual and physical sensors.
• Implementation of a multimodal interaction strategy with context-based navigation adjustments.
• Conducting an experiment with four groups evaluating task performance, self-assessment, and observational data.

Main Results:

• Participants reported enjoyment of the MR system and understood most interface elements without prior explanation.
• The interface elements, including directional arrows, obstacle indicators, and activation zones, were largely intuitive.
• Volunteers who interacted with the interface in the initial session demonstrated better comprehension.

Conclusions:

• The proposed MR-based multimodal interaction strategy effectively enhances engagement and safety in robotic gait rehabilitation.
• The developed interface elements are largely self-explanatory, facilitating intuitive use.
• Future work will focus on integrating virtual elements with the physical environment and refining the control strategy for comprehensive obstacle management.