Reconstruction for Proprioception using Tactile Arrays

Scimeca, L and Hughes, J and Maiolino, P and Iida, F. IEEE RA-L(2019) 

In collaboration with University of Cambridge

Abstract Continuum body structures provide unique opportunities for soft robotics, with the infinite degrees of freedom enabling unconstrained and highly adaptive exploration and manipulation. However, the infinite degrees of freedom of continuum bodies make sensing (both intrinsically and extrinsically) challenging. To address this, in this paper we propose a model-free method for sensorizing tentacle-like continuum soft-structures using an array of spatially arranged capacitive tactile sensors. By using visual tracking, the relationship between the tactile response and the 3D shape of the continuum soft-structure can be learned. A data set of 15000 random soft-body postures was used, with recorded camera-tracked positions logged synchronously to the tactile sensor responses. This was used to train a neural network which can predict posture. We show it is possible to achieve proprioceptive awareness over all three axis of motionin space, reconstructing the body structure and inferring the soft body head’s pose with an average accuracy of _ 1mm in comparison to the visual tracked counterpart. To demonstrate the capabilities of the system, we perform random exploration of environments limiting the work-space of the sensorized robot. We find the method capable to autonomously reconstruct the reachable morphology of the environment without the need of external sensing units.