Replication data for: Evaluation by expert dancers of a robot that performs partnered stepping via haptic interaction

In this study, we investigate the potential for a wheeled mobile robot with a human-like upper-body to perform partnered stepping with people based on the forces applied to its end effectors. The study contains relevant biomechanics data as mat files, questionnaire responses as excel files, and related python code used to run the study with the robot

Final questionnaire responses regarding overall experience.

<p>Response level of 1 = “Strongly Disagree,” 3 = “Neutral,” 5 = “Strongly Agree.” <i>p</i>-values show results from one-sample <i>t</i>-tests comparing with a response level of 3.</p

High admittance gain results in higher subjective dance performance.

<p>(A) Motor intent, (B) Motor performance, (C) Motor skill. Bars show mean and standard error. Response level of 1 = “Strongly Disagree,” 3 = “Neutral,” 5 = “Strongly Agree.”</p

Correlation between subjective and objective measures.

<p>Biomechanical measures are listed on the rows and subjective measures are listed on the columns in descending order of number of significant correlations. Black and white boxes denote significant negative and positive Pearson’s correlations coefficients, respectively. Gray denotes non-significant correlations. For example, with increasing lag, participants report that the robot follower moves and understands the leader’s motor intention less well. Also, as the interaction force increases, the participants report that the robot follower becomes less easy to communicate or move with. Similarly, as the variability in hand-sternum / CoM-CoM distance increases, the follower understands or moves according to the leader’s motor intention less accurately. Interestingly, cadence variability, RMS, and MSE values have very little correlation with any of the subjective responses. Such useful insights are possible through this correlation matrix between the biomechanical measures and subjective responses.</p

Bode plot for Low Gain, Low Stiffness.

<p>Input and output are force and velocity at the end effector, respectively. Empirical curve shows measured response of the robot. Theoretical curve shows the response of the ideal spring-damper model.</p

Glossary of dance terminology.

<p>This glossary is used for terms in the Dance Quality Questionnaire (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125179#pone.0125179.t002" target="_blank">Table 2</a>).</p><p>Glossary of dance terminology.</p

Dance Quality Questionnaire.

<p>We asked participants to respond to these questions after each experimental trial. Responses are measured using 5-point scale where 1 = “Strongly Disagree,” 3 = “Neutral,” 5 = “Strongly Agree.” The questions can be considered to fall into the three categories noted on the left column of the table, although this information was not provided to the participants.</p><p>Dance Quality Questionnaire.</p

Humans adapt force input to maintain constant velocity.

<p>(A) Humans exert 0.53x and 0.56x force at the high gain setting compared to the low gain setting when walking forward and backward, respectively. (B) Humans maintain similar velocities across all conditions. Bars show mean and standard error.</p

Acrylic rig used in the high stiffness condition.

<p>Black cloth sleeves were draped over the robot’s upper arms to conceal the presence or absence of the acrylic rig during the high stiffness and low stiffness conditions, respectively.</p

Biomechanics of human-robot partnered stepping.

<p>Example data from two cycles of one trial from one participant. Gray and white bars indicate intervals of time when right and left feet were on the ground, respectively. The experimental treatment for this trial was low gain, low stiffness.</p