This study proposed a user-tracking control algorithm for a powered wheeled walker and examined how it improves the tracking performance of a user. Our newly developed powered wheeled walker based on the mechanism of infant walker and powered wheelchair has enhanced walking stability and needs less physical power to be moved. The walker is able to smoothly track user's various movements (i.e. forward, backward translation, and rotation) using pelvis motion sensors determining walking direction and stereo cameras analyzing lower extremity motion. In particular, weighting factors of controllers using pelvis motion sensor and stereo cameras can be suitably adjustable online. The experimental testing was conducted to examine walker's tracking performance, and the results from electromyography testing showed that the walker based on user-tracking control algorithm significantly decreased the magnitude of exerted muscle strength in both upper and lower extremity compared to conventional passive wheeled walker. Thus, we were able to successfully verify that the proposed walker can automatically track a user with gait impairment for safe walking without a helper.
A conventional blind walking algorithm has low walking stability on uneven terrain because a robot cannot rapidly respond to height changes of the ground due to limited information from foot force sensors. In order to cope with rough terrain, it is essential to obtain 3D ground information. Therefore, this paper proposes a vision-guided six-legged walking algorithm for stable walking on uneven terrain. We obtained noise-filtered 3D ground information by using a Kinect sensor and experimentally derived coordinate transformation information between the Kinect sensor and robot body. While generating landing positions of the six feet from the predefined walking parameters, the proposed algorithm modifies the landing positions in terms of reliability and safety using the obtained 3D ground information. For continuous walking, we also propose a ground merging algorithm and successfully validate the performance of the proposed algorithms through walking experiments on a treadmill with obstacles.
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