02379nas a2200241   4500008004100000245011000041210006900151260000800220520153900228653002401767653001701791653002801808653002101836653001201857653001301869653001501882100001901897700001801916700002201934700001701956700002601973856013801999       2023                        eng d00aA Novel Control Law for Multi-Joint Human-Robot Interaction Tasks While Maintaining Postural Coordination0 aNovel Control Law for MultiJoint HumanRobot Interaction Tasks Wh  cOct3 a<p>Exoskeleton robots are capable of safe torque-controlled interactions with a wearer while moving their limbs through predefined trajectories. However, affecting and assisting the wearer's movements while incorporating their inputs (effort and movements) effectively during an interaction re-mains an open problem due to the complex and variable nature of human motion. In this paper, we present a control algorithm that leverages task-specific movement behaviors to control robot torques during unstructured interactions by implementing a force field that imposes a desired joint angle coordination behavior. This control law, built by using principal component analysis (PCA), is implemented and tested with the Harmony exoskeleton. We show that the proposed control law is versatile enough to allow for the imposition of different coordination behaviors with varying levels of impedance stiffness. We also test the feasibility of our method for unstructured human-robot interaction. Specifically, we demonstrate that participants in a human-subject experiment are able to effectively perform reaching tasks while the exoskeleton imposes the desired joint coordination under different movement speeds and interaction modes. Survey results further suggest that the proposed control law may offer a reduction in cognitive or motor effort. This control law opens up the possibility of using the exoskeleton for training the participating in accomplishing complex multi-joint motor tasks while maintaining postural coordination.</p>
10aBehavioral sciences10aExoskeletons10aHuman-robot interaction10aRobot kinematics10aSurveys10aTraining10aTrajectory1 aGhonasgi, Keya1 aMirsky, Reuth1 aHaith, Adrian, M.1 aStone, Peter1 aDeshpande, Ashish, D.  uhttps://reneu.robotics.utexas.edu/novel-control-law-multi-joint-human-robot-interaction-tasks-while-maintaining-postural-coordination01991nas a2200241   4500008004100000245008800041210006900129260000800198520119100206653002901397653001701426653001001443653002801453653002401481653001501505653001301520100001901533700001801552700002201570700001701592700002601609856011401635       2022                        eng d00aQuantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System0 aQuantifying Changes in Kinematic Behavior of a HumanExoskeleton   cOct3 a<p>While human-robot interaction studies are becoming more common, quantification of the effects of repeated interaction with an exoskeleton remains unexplored. We draw upon existing literature in human skill assessment and present extrinsic and intrinsic performance metrics that quantify how the human-exoskeleton system's behavior changes over time. Specifically, in this paper, we present a new performance metric that provides insight into the system's kinematics associated with ‘successful’ movements resulting in a richer characterization of changes in the system's behavior. A human subject study is carried out wherein participants learn to play a challenging and dynamic reaching game over multiple attempts, while donning an upper-body exoskeleton. The results demonstrate that repeated practice results in learning over time as identified through the improvement of extrinsic performance. Changes in the newly developed kinematics-based measure further illumi-nate how the participant's intrinsic behavior is altered over the training period. Thus, we are able to quantify the changes in the human-exoskeleton system's behavior observed in relation with learning.</p>
10aAtmospheric measurements10aExoskeletons10aGames10aHuman-robot interaction10aInteractive systems10aKinematics10aTraining1 aGhonasgi, Keya1 aMirsky, Reuth1 aHaith, Adrian, M.1 aStone, Peter1 aDeshpande, Ashish, D.  uhttps://reneu.robotics.utexas.edu/quantifying-changes-kinematic-behavior-human-exoskeleton-interactive-system