Human-Following Control of Cane-Type Walking-Aid Robot Within Fixed Relative Posture

Assisting and supervising daily long-durational walking is very crucial for patients with lower extremity dysfunction, especially in the stage of recovery toward a state of walking independently. However, due to the shortage of caregivers and high cost of nursing, long-term manual assistance and supervision is costly. Thus, in this article, we propose a cane-type walking-aid robot to follow a human user for the safety and supervision of independent walking during rehabilitation training. Strongly motivated by clinical suggestions and user experiences, the human-following rule that the robot should follow the user in the required position within a fixed relative posture (keeping a certain distance in front of the user, 15–20 cm lateral to the healthy side, and 0
$^{\circ }$
to the user’s orientation) is established. To guarantee a reliable following, a quantitative human walking intention estimation method is proposed using the on-board laser ranger finder and Kalman filter. To effectively monitor the user’s walking, a finite-time control method for the cane robot is also proposed to ensure its human-following performance. Experiments were conducted to demonstrate the effectiveness of the proposed system and methods. The experimental results show that the proposed system can obtain satisfactory performance of human following and can be made available for different users in different walking modes.