A review on interaction control for contact robots through intent detection

Publication information for article A review on interaction control for contact robots through intent detection</p

Adapting the visuo-haptic perception through muscle coactivation

Publication information for article Adapting the visuo-haptic perception through muscle coactivation.</p

Simulation of dyadic reaching.

<p>Trajectories and torques from dyads I to IV (A–D) in the coupled and push-pull blocks. Solid trace is from the data showing the mean of all trials and the shaded area is the 95% confidence interval; the dashed traces are from simulations. First, we identify the state costs of both partners in coupled reaching, then identify the state cost in the push-pull blocks to see what effect the opposing torques prior to movement onset had. In all dyads, the initial opposing torque had a consistent effect: partners pushing towards the target prioritised position, and overshot the target; those pulling away prioritised velocity and undershoot the target.</p

Position and velocity priority in the motion plan explains endpoint bias.

<p>(A) The (decoupled) blue controller prioritises position, which causes it to overshoot the target. The (decoupled) red controller prioritises velocity such that it converges to the target without any overshoot. When the position-priority and velocity-priority controllers are coupled (dashed black trace), a force pattern is observed (dashed blue and red traces). The only manner in which the controllers would end the movement with constant torque is if they decide to hold their position once the reach is fulfilled. (B) Endpoint bias at the end of the reaching movement from all 16 partners. Partners, at movement onset, who pushed towards the target overshot it, and those who pulled away undershot it.</p

Dyadic reaching with initial opposing torque prior to movement.

<p>Torque from dyads I–IV in the coupled and both push-pull blocks; each bold trace is the average trajectory of each bin. In all dyadic reaching blocks, the torque was unchanging between trials within each block.</p

Experimental setup: participants pressed with a finger (index or little) of both left and right hands on isometric force transducers.

<p>The subjects were required to match the goal force level (a horizontal line in the central bar) as accurately as possible with the summation of each finger’s force level (summation of the force levels is given by the LEDs in the central bar and the individuals’ force levels of the left and right hand are given by the left and right bars, respectively).</p

Mean and standard deviation over all participants for the coefficient of variation measured in our experiments and in [10]. All measurements are in Newtons (N).

<p>Mean and standard deviation over all participants for the coefficient of variation measured in our experiments and in [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0149512#pone.0149512.ref010" target="_blank">10</a>]. All measurements are in Newtons (N).</p

The via-point movements are spontaneously performed using multiple solutions.

<p>A) shows the trajectory solutions employed by two representative subjects in setups A and B, respectively. The trajectories in the three orientations have been separated out and placed in a radial arrangement for clarity. The difference in EMG patterns in six arm muscles between the two solutions is shown for a third subject in the individual orientations. The free trajectories of a third subject (B) show three different trajectories utilized in different proportions (pie chart) in the different orientations (arc bars). Following an exploration of SOL2 (C), the proportion of SOL2 increases dramatically in each orientation (arc bars) and in total (pie chart), showing an increase also in the unexplored orientation (grey). Subsequently, the free trials after exploration of SOL1 (D) show an increase of SOL1 in all orientations again. This effect was consistent across subjects (E) in both setups. The peripheral bar charts of (E) show the change in SOL1 and SOL2 across all subjects in the two explored and in the unexplored (grey) orientations. The central bar chart combines data from all orientations. Individual subject data is represented by the green traces.</p

Definition of main kinds of behaviors (in interactive tasks) through cost functions.

<p>For simplicity, the time variable was omitted in the cost functions.</p

Fitted (x-axis) versus produced forces (y-axis) based on the assumption that only variability was optimized (left) and under the best fitting model (right) and force target 18N (top), 22N (middle) and 26N (bottom).

<p>Fitted (x-axis) versus produced forces (y-axis) based on the assumption that only variability was optimized (left) and under the best fitting model (right) and force target 18N (top), 22N (middle) and 26N (bottom).</p