Human-Human Hand Interactions Aid Balance During Walking by Haptic Communication

Principles from human-human physical interaction may be necessary to design more intuitive and seamless robotic devices to aid human movement. Previous studies have shown that light touch can aid balance and that haptic communication can improve performance of physical tasks, but the effects of touch between two humans on walking balance has not been previously characterized. This study examines physical interaction between two persons when one person aids another in performing a beam-walking task. 12 pairs of healthy young adults held a force sensor with one hand while one person walked on a narrow balance beam (2 cm wide x 3.7 m long) and the other person walked overground by their side. We compare balance performance during partnered vs. solo beam-walking to examine the effects of haptic interaction, and we compare hand interaction mechanics during partnered beam-walking vs. overground walking to examine how the interaction aided balance. While holding the hand of a partner, participants were able to walk further on the beam without falling, reduce lateral sway, and decrease angular momentum in the frontal plane. We measured small hand force magnitudes (mean of 2.2 N laterally and 3.4 N vertically) that created opposing torque components about the beam axis and calculated the interaction torque, the overlapping opposing torque that does not contribute to motion of the beam-walker’s body. We found higher interaction torque magnitudes during partnered beam-walking vs. partnered overground walking, and correlation between interaction torque magnitude and reductions in lateral sway. To gain insight into feasible controller designs to emulate human-human physical interactions for aiding walking balance, we modeled the relationship between each torque component and motion of the beam-walker’s body as a mass-spring-damper system. Our model results show opposite types of mechanical elements (active vs. passive) for the two torque components. Our results demonstrate that hand interactions aid balance during partnered beam-walking by creating opposing torques that primarily serve haptic communication, and our model of the torques suggest control parameters for implementing human-human balance aid in human-robot interactions.

Kinematic compatibility of a wrist robot with cable differential actuation: effects of misalignment compensation via passive joints

<div><div><div><p>We present the UDiffWrist (UDW), a low-impedance 2-DOF wrist exoskeleton featuring a cable-differential transmission. To investigate the effect of different design strategies for achieving kinematic compatibility, we developed two versions of this robot: One version (UDW-C) achieves kinematic compatibility only in the case of perfect alignment between human and robot joints. The second version (UDW-NC) connects the human and robot via passive joints to achieve kinematic compatibility regardless of alignment between human and robot joints. Through characterization experiments, we found that the UDW-NC was more robust to misalignments than the UDW-C: the increase in maximum interaction torque associated with misalignments was greater for the UDW-C than the UDW-NC robot (p = 0.003). However, the UDW-NC displayed greater Coulomb friction (p < 0.001). Further, Coulomb friction increased more for the UDW-NC than the UDW-C in the presence of misalignments between the human and robot axes (p < 0.001). We also found that torque transfer was more accurate in the UDW-C than in the UDW-NC. These results suggest that for the small (10 deg) 2-DOF wrist movements considered, the advantages of the UDW-NC in terms of kinematic compatibility are likely overshadowed by the negative effects in friction and torque transfer accuracy.</p></div></div></div>

Kinematic compatibility of a wrist robot with cable differential actuation: effects of misalignment compensation via passive joints

<div><div><div><p>We present the UDiffWrist (UDW), a low-impedance 2-DOF wrist exoskeleton featuring a cable-differential transmission. To investigate the effect of different design strategies for achieving kinematic compatibility, we developed two versions of this robot: One version (UDW-C) achieves kinematic compatibility only in the case of perfect alignment between human and robot joints. The second version (UDW-NC) connects the human and robot via passive joints to achieve kinematic compatibility regardless of alignment between human and robot joints. Through characterization experiments, we found that the UDW-NC was more robust to misalignments than the UDW-C: the increase in maximum interaction torque associated with misalignments was greater for the UDW-C than the UDW-NC robot (p = 0.003). However, the UDW-NC displayed greater Coulomb friction (p < 0.001). Further, Coulomb friction increased more for the UDW-NC than the UDW-C in the presence of misalignments between the human and robot axes (p < 0.001). We also found that torque transfer was more accurate in the UDW-C than in the UDW-NC. These results suggest that for the small (10 deg) 2-DOF wrist movements considered, the advantages of the UDW-NC in terms of kinematic compatibility are likely overshadowed by the negative effects in friction and torque transfer accuracy.</p></div></div></div>

Trends in Haptic Communication of Human-Human Dyads: Toward Natural Human-Robot Co-manipulation

In this paper, we analyze and report on observable trends in human-human dyads performing collaborative manipulation (co-manipulation) tasks with an extended object (object with significant length). We present a detailed analysis relating trends in interaction forces and torques with other metrics and propose that these trends could provide a way of improving communication and efficiency for human-robot dyads. We find that the motion of the co-manipulated object has a measurable oscillatory component. We confirm that haptic feedback alone represents a sufficient communication channel for co-manipulation tasks, however we find that the loss of visual and auditory channels has a significant effect on interaction torque and velocity. The main objective of this paper is to lay the essential groundwork in defining principles of co-manipulation between human dyads. We propose that these principles could enable effective and intuitive human-robot collaborative manipulation in future co-manipulation research.

Single Leg Gait Tracking of Lower Limb Exoskeleton Based on Adaptive Iterative Learning Control

The lower limb exoskeleton is a wearable human–robot interactive equipment, which is tied to human legs and moves synchronously with the human gait. Gait tracking accuracy greatly affects the performance and safety of the lower limb exoskeletons. As the human–robot coupling systems are usually nonlinear and generate unpredictive errors, a conventional iterative controller is regarded as not suitable for safe implementation. Therefore, this study proposed an adaptive control mechanism based on the iterative learning model to track the single leg gait for lower limb exoskeleton control. To assess the performance of the proposed method, this study implemented the real lower limb gait trajectory that was acquired with an optical motion capturing system as the control inputs and assessment benchmark. Then the impact of the human–robot interaction torque on the tracking error was investigated. The results show that the interaction torque has an inevitable impact on the tracking error and the proposed adaptive iterative learning control (AILC) method can effectively reduce such error without sacrificing the iteration efficiency.