Fig 1.
The figure illustrates the experimental setup used for performing the accuracy assessment.
From the left to the right the figure display: a view of the robotic arm, where all the 7 DoF axes are indicated; the definition of the world (W) and the end-effector (E) coordinate frames of the robot; the custom tool devised with the fixation mechanism used to rigidly attach the 6 IMUs to the robotic system; the 3 different configuration of the robotic arm used in the experimental protocol.
Table 1.
Matrix of movement trials for dynamic accuracy validation expressed as (± amplitude in degrees, frequency in Hz): amplitudes are varied row–wise and frequencies are varied column-wise.
Fig 2.
The boxplots represent absolute (left) and relative (right) accuracies for the pure static(PS) trial of static part of the protocol.
The first and the second bar report respectively the data obtained by using the KF and the CF algorithm.
Fig 3.
Results for the static after motion (SaM) trial: the solid line represents the median of the orientation error (i.e. the distance from the estimate at convergence) and its associated inter quartile range (colored shadow).
Graphs are organized according to the type of trial, heading), the sensor fusion algorithm selected (KF or CF) and the type of dynamic movement considered (slow and fast).
Fig 4.
The figure reports the dynamic absolute accuracy absolute obtained with the KF algorithm (left column) and CF algorithm (right column).
It is represented as the 95% error range (colored box) and the median value of results (solid black line).
Fig 5.
The figure reports the relative accuracy obtained with the KF algorithm (left column) and CF algorithm (right column).
It is represented as the 95% error range (colored box) and the median value of results (solid black line).
Fig 6.
The figure reports the trend in the absolute orientation error computed with the KF, for varying movement frequency (top) and range of motion (bottom).
Data are represented as the median value (red line), IQR (blue box) and minimum and maximum values (black whiskers). Outliers are removed from each dataset using a ±3 IQR threshold: respectively 55 and 53 datapoints out of 19440 from the top and the bottom graph.
Fig 7.
The figure reports the trend in the absolute orientation error computed with the CF, for varying movement frequency (top) and range of motion (bottom).
Data are represented as the median value (red line), IQR (blue box) and minimum and maximum values (black whiskers). Outliers are removed from each dataset using a ±3 IQR threshold: respectively 16 and 32 datapoints out of 19440 from the top and the bottom graph.