The aging population phenomenon is increasing daily, making the realization of robots to help the elderly via human-robot collaboration an urgent need. However, in terms of the current research, there are many challenges in the realization of collaborative systems applied to help the elderly. The interaction methods used in related studies are single and unfavorable for the elderly, which not only affects the understanding of users' intentions but also brings burdens to the elderly. Moreover, these approaches generally ignore the flexibility of the division of labor and the degree of human need for assistance, which reduces the performance of goal completion and affects the elderly's evaluation of the robot escort. To this end, this paper designs and implements a human-robot collaboration system for helping the elderly (HRCS_EE). A multimodal fusion algorithm based on understanding and supplemented by inquiry is proposed. Additionally, a collaborative division strategy based on a cognitive model is researched, and a decision-making algorithm that aims to achieve the most efficient completion of collaborative tasks and minimize the burden on people is proposed. Finally, the method is verified and applied in a human-robot collaboration system based on repeated interaction. The experimental results show that the system can accurately and reliably obtain users' intentions in complex environments and correctly make division of labor decisions in line with the environment, so that the robot can provide the assistance that is truly needed by the elderly, which is well received by users.

This paper investigates the curve path following problem for a class of planar underactuated bio-inspired snake robots. The time-varying line-of-sight (LOS) guidance law and the cubic spline interpolation (CSI) path-planning method are employed. Existing studies focus on straight line path following which only gives a solution for snake robot motion control in relatively simple environments. Considering the snake robot's many degrees of freedom and excellent mobility in terrains, we propose a more applicable solution of curve path following for snake robots on the ground. The improved LOS helps the snake robot to steer aggressively at a sharp turning point. Furthermore, to avoid the sideslip of the snake robot caused by the ground friction change, an integral controller is introduced in the design of the heading reference. Simulations and experiments on an 8-link custom-built snake robot are conducted and the results demonstrate and validate the effectiveness of the proposed curve path following algorithm.

This paper investigates the straight path following problem for a class of underactuated bio-inspired snake robots on ground with unknown and varied friction coefficients. Existing works usually design control input requiring the exact values of these friction coefficients, which however rely on the specific operating terrain and may not always be known a priori. By virtue of backstepping technique, we present a novel adaptive controller that can compensate for unknown and varied friction coefficients in real-time. Moreover, it is proved via LaSalle-Yoshizawa theorem that the path following errors converge to zero asymptotically and all the parameter estimates are bounded. Simulations and experiments on an 8-link snake robot are carried out to illustrate the effectiveness of the proposed controller.