Journal Papers

KAIST Exoskeleton Lab

2025 Inertial Orientation Estimation Robust to Impact for Bipedal Robot Locomotion

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Author
Jinsu Park, Taeyeon Kim, Kyoungchul Kong
Journal
International Journal of Control, Automation and Systems
Volume
23
Number
4
Page
1139-1146
Year of publication
2025

Abstract:

The inertial measurement unit (IMU) sensor is widely used to estimate the orientation of bipedal robots. Many filters have been developed based on Kalman filters and complementary filters to improve orientation estimation. However, most existing filters do not account for the rapidly changing dynamic characteristics and impact forces encountered in bipedal robot locomotion. To address this limitation, an adaptive inertial orientation estimation filter is introduced, which dynamically adjusts its parameters in response to detected impacts. A real-time algorithm for impact detection is also proposed to enhance the filter’s performance. The proposed filter was tested under walking conditions at various speeds, encompassing both low-impact and high-impact scenarios commonly observed in bipedal robot locomotion. Results demonstrated that as walking speed increased and ground impact forces became more pronounced, the proposed filter exhibited superior accuracy compared to conventional filters. This filter, in combination with real-time impact detection algorithms, provides a reliable framework for improving orientation estimation in bipedal robots.