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Updated: May 25, 2026
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Fully Automated Leg Tracking in Freely Moving Insects using Feature Learning Leg Segmentation and Tracking (FLLIT)
Published on: April 23, 2020
INS/EKF-based stride length, height and direction intent detection for walking assistance robots.
Dario Brescianini1, Jun-Young Jung, In-Hun Jang
1Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland. bdario@student.ethz.ch
Summary
This study presents an algorithm for exoskeleton robots to detect user intent for walking assistance. The system uses inertial measurement units on crutches and an extended Kalman filter for accurate gait pattern generation.
Area of Science:
- Robotics
- Biomechanics
- Assistive Technology
Background:
- Paraplegic patients require advanced assistive devices for mobility.
- Exoskeleton robots offer a promising solution for gait restoration.
- Accurate real-time intent detection is crucial for effective exoskeleton control.
Purpose of the Study:
- To develop an algorithm for determining user's stride length, height difference, and walking direction.
- To enable exoskeleton robots to generate on-line gait patterns for paraplegic users.
- To improve the naturalness and responsiveness of robotic gait assistance.
Main Methods:
- An inertial measurement unit (IMU) was attached to crutches.
- An extended Kalman filter was employed for error correction and drift reduction.
- The algorithm was validated in real-world walking scenarios.
Main Results:
- The algorithm successfully obtained stride length, height difference, and direction information.
- The extended Kalman filter effectively mitigated IMU bias and drift.
- The system demonstrated reliable performance during walking, stair climbing, and direction changes.
Conclusions:
- The proposed algorithm enables accurate user intent recognition for exoskeleton gait assistance.
- The method enhances the capability of exoskeleton robots to adapt to user's needs in real-time.
- This technology holds potential for improving the mobility and independence of individuals with paraplegia.
