Improving Interactions between a Power-Assist Robot System and Its Human User in Horizontal Transfer of Objects Using a Novel Adaptive Control Method

Abstract

Power assist systems are usually used for rehabilitation, healthcare, and so forth.This paper puts emphasis on the use of power assist systems for object transfer and thus brings a novelty in the power-assist applications. However, the interactions between the systems and the human users are usually not satisfactory because human features are not included in the control design. In this paper, we present the development of a 1-DOF power assist system for horizontal transfer of objects. We included human features such as weight perception in the system dynamics and control. We then simulated the system using MATLAB/Simulink for transferring objects with it and (i) determined the optimum maneuverability conditions for object transfer, (ii) determined psychophysical relationships between actual and perceived weights, and (iii) analyzed load forces and motion features. We then used the findings to design a novel adaptive control scheme to improve the interactions between the user and the system. We implemented the novel control (simulated the system again using the novel control), the subjects evaluated the system, and the results showed that the novel control reduced the excessive load forces and accelerations and thus improved the human-system interactions in terms of maneuverability, safety, and so forth. Finally, we proposed to use the findings to develop power assist systems for manipulating heavy objects in industries that may improve interactions between the systems and the users.

Calibrating intuitive and natural human–robot interaction and performance for power-assisted heavy object manipulation using cognition-based intelligent admittance control schemes

“…The results show that the VAC was more effective to produce higher HRI and performance for power-assisted manipulation than the MPC . 9,23,29 It happened because the VAC was empirical but more natural than the MPC. The MPC attempted to reduce the excess in the PLF through computing a predicted input to produce a predicted output based on optimization, which might not reflect human’s intent, and also the mapping between the input and the output might not be perfect due to nonlinearities in the PARS.…”

“…15,16,18 We posit that the subjective evaluation can be complementary to objective evaluation in such cases. 18 In addition, the evaluation of HRI should include both physical HRI (pHRI) 22,23 and cognitive HRI (cHRI). 24 However, a holistic scheme to evaluate HRI and performance is not available, and optimization strategies to produce optimum HRI and performance are still not proposed for object manipulation with power assist except preliminary initiatives taken by Rahman and Ikeura.…”

Power Assist Rehabilitation Robot and Motion Intention Estimation

“…Other drawbacks of conventional power assist systems for object manipulation include the lack of human characteristics in control, the system's weight, the quantity of power aid being unclear, and the system's safety, mobility, and efficiency not being properly analyzed, among others. Conventional power assist devices, on the other hand, do not take a holistic approach to tackle these problems/issues to make systems more human-friendly [48].…”