System’s variables.

<p>System’s variables.</p

Examples of posterior distribution of nodule’s depth estimation across iterations.

<p>Each plot depicts the distribution of depth estimation from the initially defined flat distribution at <i>t</i> = 0 to <i>t</i> = 5 given different combinations of probe’s stiffness, indentation, and PSV. The real depths of nodule, <i>d</i>_<i>r</i>, assessed here were those known values associated with the memory primitives explained earlier.</p

Embodiment mediates both perception and action during the interaction between an agent and the environment.

<p>The system interacts with the environment through its embodiment. The internal impedance required for accurate perception through its embodied sensor can differ from that required to take appropriate action. Likewise an action taken with appropriate impedance could affect the quality of perception of the environment.</p

Nodule’s depth estimation accuracy across <i>i</i>.

<p>Nodule’s depth estimation accuracy across <i>i</i>.</p

Three dimensional design of the robotic probe and photos of experimental setup and sample soft silicon phantom.

<p>(a) Shaded view of two-link probe’s design. (b) Two springs located inside the spring chambers are attached with the anchor ring and the pivot joint through a microfilament thread. (Note that the springs shown here are for illustrative purpose only). The stiffness of the joint can be represented by the distance of <i>r</i>_<i>a</i>. (c) Photo of the complete experimental platform’s design comprising of the variable stiffness probe mounted on XY-stage. (d) A soft silicon phantom fabricated using soft clear silicon elastomer gel with a spherical plastic bead of size 15mm diameter embedded inside at different depths.</p

The nodule’s depth estimation accuracy under fixed-5-iteration Bayesian inferencing algorithm.

<p>The resulting overall nodule’s depth estimation accuracy is shown in black line. The estimation accuracy for each actual depth, <i>d</i>_<i>r</i> = 2, 4, and 8 mm are shown in red, green and magenta lines respectively.</p

Simulated joint torque and stiffness.

<p>Torque (a) and the stiffness (b) produced at the pivot joint due to the changes in the displacement of the anchor ring, <i>r</i>_<i>a</i>, and the angular displacement of the joint, <i>q</i>.</p

Sample of muscle activity at FDS and EDC during human’s manual palpation.

<p>The FDS (a) and EDC (b) muscle activities were quantified by the EMG signal during manual palpation trial to estimate the depth of a hard nodule embedded inside a silicon phantom. The combination of the activities contributed from both muscles can be described as the co-contraction. The normalised co-contraction is shown in magenta curve in (c); whereas the red circles indicate the peaks extracted from this signal.</p

Experimental Conditions.

<p>Experimental Conditions.</p

Overall nodule’s depth estimation accuracy when using different approaches.

<p>1) 5-iteration Bayesian inference without KL-divergence (shown in green), 2) the Bayesian Inference together with the KL-Transfer Entropy with fixed probe’s stiffness, indentation level, and PSV (shown in orange), and 3) the Bayesian Inference together with the KL-Transfer Entropy with random probe’s stiffness, indentation level, and PSV (shown in blue).</p