Exoskeleton provides personalized hip haptic cues for blind navigation
XoNav: An Exoskeleton as a Personalized Haptic Interface for Assisted Navigation
Robotics
Summary
Walking without sight is hard because people need clear and quick signals to tell them where to go. The authors built a wearable device with motors on the hips that give gentle taps to show when to move forward, stop, or turn. It uses sensors on the legs to know when a person is walking and sends the signals at the right times. People who tried it could easily tell different signals and walk accurately while blindfolded. The device also showed promise for helping with autonomous navigation around obstacles.
What this means in practice
- •For assistive device makers: Develop hip-worn wearable aids that provide real-time walking guidance through haptic signals tailored to users’ gait patterns.$Commercial implications: Enables new personalized exoskeleton products for visually impaired users offering intuitive navigation support.
- •For robotic navigation teams: Combine body-worn cameras and mapping with wearable haptic feedback for human-robot collaborative navigation in unknown environments.
Authors
Debadrata Sarkar, Soumen Sen, Aman Arora
Abstract
Walking without vision requires timely, unambiguous guidance, yet many wearable aids encode directions as audio or vibrotactile signals that users must translate into movement. We present XoNav, a four-actuator hip exoskeleton that renders guidance cues directly at the hip joints. It renders an Advance cue and two-level Braking cues through sagittal-plane actuators and two-level Steering cues through frontal-plane actuators. A bilateral LSTM-based gait-state classifier uses two thigh-mounted IMUs to identify gait states, enabling haptic cues to be delivered in coordination with the wearer's gait while suppressing them during standing. The classifier generalized to unseen users with recalls of 95.2-97.9%, with mean detection delays of 38.6 and 63.1 ms for stance-to-swing and swing-to-stance transitions, respectively. Constrained human-in-the-loop Bayesian optimization personalized Braking for minimum resistance and Steering for maximum comfort while ensuring detectability and safety. All participants reliably distinguished between grades of their personalized cues and the firmest Braking cue remained below 53% of the safety limit. In blindfolded Wizard-of-Oz navigation trials along three paths, the participants kept 98.8% of the walked distance within a 0.75 m wide passage, with a 4.9% increase in mean progression speed per trial. A body-worn camera, RTAB-Map and Nav2 further enabled a feasibility study of autonomous navigation and detours around previously unmapped obstacles.