For quadruped guide robots assisting visually impaired users, accurate estimation of the user’s applied force is essential for safe navigation. However, precise force estimation is hindered by periodic noise induced by robot locomotion. Conventional filtering methods, such as Low-Pass Filters (LPF), often fail to separate these signals effectively. These methods tend to over-smooth the signal, resulting in significant distortion or attenuation of interaction forces. To address this problem, this paper proposes a proprioception-based external force estimation method that utilizes gait phase and contact information. By synchronizing the estimation with the robot’s stepping cycle, the proposed approach selectively mitigates locomotion-induced disturbances without compromising signal fidelity. Experimental results demonstrate that the proposed method effectively removes gait-induced noise while preserving the magnitude of user interactions. Consequently, the proposed approach exhibits superior estimation accuracy compared to conventional baselines.
Estimation accuracy, External force estimation, Filtering method, Human robot interaction(HRI), Interaction forces, Low pass filter(LPF), Robot locomotion, Safe navigation, User interaction, accurate estimation, estimation method
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