Multimodal Bioinspired Artificial Skin Module for Tactile Sensing - Alves de Oliveira, Thiago Eustaquio (Université d'Ottawa / University of Ottawa, 2019)
Tactile sensors are the last frontier to robots that can handle everyday objects and interact with humans through contact. Robots are expected to recognize the properties of objects in order to handle them safely and efficiently in a variety of applications, such as health- and elder care, manufacturing, or high-risk environments. To be effective, such sensors have to sense the geometry of touched surfaces and objects, as well as any other relevant information for their tasks, such as forces, vibrations, and temperature, that allow them to safely and securely interact within an environment. Given the capability of humans to easily capture and interpret tactile data, one promising direction in order to produce enhanced robotic tactile sensors is to explore and imitate human tactile sensing capabilities. In this context, this thesis presents the design and hardware implementation issues related to the construction of a novel multimodal bio-inspired skin module for dynamic and static tactile surface characterization. Drawing inspiration from the type, functionality, and organization of cutaneous tactile elements in the human skin, the proposed solution determines the placement of two shallow sensors (a tactile array and a nine DOF magnetic, angular rate, and gravity system) and a deep pressure sensor within a flexible compliant structure, similar to the receptive field of the Pacinian mechanoreceptor. The benefit of using a compliant structure is tri-folded. First, the module has the capability of performing touch tasks on unknown surfaces, tackling the tactile inversion problem. The compliant structure guides deforming forces from its surface to the deep pressure sensor, while keeping track of the deformation of the structure using advantageously placed shallow sensors. Second, the module’s compliant structure and its embedded sensor placement provide useful data to overcome the problem of estimating non-normal forces, a significant challenge for the current generation of tactile sensing technologies. This capability allows accommodating sensing modalities essential for acquiring tactile images and classifying surfaces by vibrations and accelerations. Third, the compliant structure of the module also contributes to the relaxation of orientation constraints of end-effectors or other robotic parts carrying the module to contact surfaces of unknown objects. Issues related to the module calibration, its sensing capabilities and possible real-world applications are also presented.
Keywords: Tactile Sensing; Touch Sensing; Haptics; Bioinspired Robotics; Surface Reconstruction