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BIOMIMETIC TACTILE SENSOR
FOR OBJECT IDENTIFICATION
AND GRASP CONTROL
by
Nicholas B. Wettels
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(BIOMEDICAL ENGINEERING)
May 2011
Copyright 2011 Nicholas B. Wettels
Object Description
| Title | Biomimetic tactile sensor for object identification and grasp control |
| Author | Wettels, Nicholas B. |
| Author email | nick.wettels@gmail.com; nick.wettels@syntouchllc.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Biomedical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2010-12-17 |
| Date submitted | 2011 |
| Restricted until | Unrestricted |
| Date published | 2011-05-06 |
| Advisor (committee chair) |
Loeb, Gerald E. Valero-Cuevas, Francisco |
| Advisor (committee member) |
Weiland, James Schaal, Stefan |
| Abstract | PROBLEM STATEMENT. One of the severe performance limitations of robotic and prosthetic hands in unstructured environments is their having little or no tactile information compared to the rich tactile feedback of the human hand. Object interaction involves two senses: proprioceptive (information about force and pose of joints of a manipulator) and cutaneous (information from the skin or sensors near the surface of the manipulator's end-effector). The discussion of tactile sensing here will surround problems and solutions based largely cutaneous sensing inspired by the human fingertip.; This necessity of tactile information is obvious in clinical cases where patients that suffer peripheral nerve damage to their hands are able to initiate, but not maintain stable grasp due to lack of sensory feedback from cutaneous sensors (Rothwell 1982). Neurophysiologists have identified that rapid reflexive adjustment of grip is essential for handling objects and depends on tactile feedback via the spinal cord (Westling & Johansson, 1984). Autonomous robots can deal only with rigid objects in known orientations specifically because they lack tactile feedback. Engineers developing telerobotic manipulators have also improved performance when force and vibrotactile feedback is provided via "haptic displays" to the operator's hand (Kontarinis & Howe, 1995).; Advancements in sensor hardware will undoubtedly catalyze equally important advancements in controller design and grasp planning algorithms. Numerous fields of research would benefit from such advances: anthropomorphic robotics, tele-operated and autonomous robotics, robotic and telesurgery, telediagnostics, diagnostic palpation and prosthetic limbs. With respect to upper limb prosthesis, 58.5% of the 1,199,111 patients from 1988 to 1996 were upper limb amputees (Dillingham et al. 1998).; As mentioned, one of the limiting factors in all of these applications has been the absence of sensitive yet robust sensors that can be incorporated into anthropomorphic mechatronic fingers. A wide variety of technologies have been applied to the cutaneous tactile sensing problem in robotics and medicine. Transduction mechanisms such as optics, capacitance, piezoresistance, ultrasound, conductive polymers, etc. have all yielded viable solutions but only for limited environments or applications. These solutions often result in large numbers of delicate transducers and connections that are unable to survive the often hostile environments in which the hands function. Additionally, the sensors may not possess all the modalities necessary for a tactile sensor to support grip control or object identification.; DESCRIPTION OF SOLUTION. Here we describe a biomimetic tactile sensor that is sensitive to the wide range of normal and shear forces encountered in robotic and prosthetic applications. It is intrinsically simple, robust, and easy to manufacture and repair. The elastomeric skin is resistant to wear, and possesses texture and tackiness similar to the properties of human skin that facilitate grip. The curved, deformable nature of biological finger tips provides mechanical features that are important for the manipulation of the wide variety of objects encountered naturally. Electrodes are distributed along the surface of the rigid core and all sensitive components are safely embedded within the core. By applying an alternating current to each contact, one can measure the impedance of each volumetric flow path from a given contact to a reference electrode. Several factors will affect the resting impedance of an electrode: electrode size, material, fill volume, skin geometry, excitation frequency and fluid resistivity. External forces deform the fluid path around the electrodes, resulting in a distributed pattern of impedance changes containing information about force magnitude, direction, point of contact and object shape (Wettels et al. 2008a).; Because the conductivity of the fluid or gel increases with temperature, a thermistor is incorporated for thermal compensation. Furthermore, the fluid can be heated; when objects contact the device heat will be transferred according to the thermal and geometric properties of the object. Thus material information about the object can be extracted using heat-flow information, as biological finger tips do.; A hydrophone (pressure sensor) can also be mounted to the fluid channel of the sensor to gather acoustic information about contacted objects. Objects that slip will produce a high-frequency stick-slip phenomenon between the skin and the object; these high-frequency vibrations will be transmitted through the fluid and can be measured by the hydrophone. Objects with textures and surface features finer than the resolution of the impedance sensors will also produce a similar acoustic phenomenon within the fluid as the sensor haptically explores objects (Fishel et al. 2008). We posit material information from texture can be gathered from these data as well.; Here we will show that it is necessary to possess all three sensing modalities in order to make an accurate assessment of object properties. For example, if heat-flow sensing is used to gather information about a contacted object's thermal properties, one must calibrate the data with the force sensing modality, because surface area of contact, point of contact, object geometry and time of contact all impact the heat-flow signature.; What remains to be determined is how the data will be used, which is not entirely clear. In the biological system, direct computation of the measured percept occurs (e.g. your fingertips and brain do not calculate Newtons), but these systems must obviously encode forces for proper manipulation. The question then becomes, how do we utilize data from non-linear sensors such as the BioTac? Shall their outputs be linearized using machine learning and/ or curve-fitting techniques so they can be employed as commercial sensors, or is there a solution akin to biological systems?; STRUCTURE OF DISSERTATION. This discussion is separated into six chapters. In chapter one we outline the specific problems we are trying to solve in tactile sensing, the state of the art and the requirements to solve those problems. In chapter two we discuss the decision making process regarding the material choices for the core, skin and fluid and how these choices lend to meeting the requirements and constraints outlined in chapter one. Chapter three continues the discussion by taking these material constraints and demonstrating how design considerations evolved into the fabrication and testing practices that produced simple prototypes to the current sensors ready to be equipped on mechatronic manipulanda. Chapter four explores the notion of how to use the data produced by the sensor's force detection modality. This chapter focuses on how machine learning and heuristics can be used to extract radius of curvature, point of application of force and explicit force vectors. This is done not only match commercial sensor usage, but to show that these data are in fact embedded in the non-linear processes of the BioTac. Chapter five is a validation of sensor performance on a prosthetic hand. This involves normal and tangential force extraction using a Kalman filter for a constrained grip control task. Chapter six consists of preliminary experiments to thermally characterize objects using the heat-flow sensing modality. The paper ends with a discussion of how this work fits into the field of haptics and how the tactile signals can be used for conscious feedback of sensation for a prosthetic, reflexive grip control for a mechatronic hand and object property identification algorithms for robotic systems.; The chapters in this thesis are based on published or journal articles in progress:; Chapter one is based on unpublished and published work: -- Wettels N., Santos V. J., Johansson R. S, and Loeb G. E., "Biomimetic tactile sensor array." Advanced Robotics, vol. 22, no. 7 pp. 829–849, June 2008.; Chapter two is based on unpublished work; select material to be submitted to Journal of Applied Polymer Science.; Chapter three includes unpublished results and is based on work that has been published and appears in Appendix A and B: -- Wettels N., Santos V. J., Johansson R. S, and Loeb G. E., "Biomimetic tactile sensor array." Advanced Robotics, vol. 22, no. 7 pp. 829–849, June 2008. -- Wettels N., Smith L.M., Santos V.J., and Loeb G. E., Deformable Skin Design to Enhance Response of a Biomimetic Tactile Sensor, in Proc. of International Conference on Biomedical Robotics and Biomechatronics, Scottsdale, Arizona, 2008b.; Chapter four is based on work that is unpublished and published work (Appendix C); select material to be submitted to International Journal of Robotics Research: -- N. Wettels, J.A. Fishel, Z. Su, C.H. Lin, and G.E. Loeb. "Multi-modal Synergistic Tactile Sensing" Tactile Sensing in Humanoids – "Tactile Sensors and Beyond Workshop 9th IEEE-RAS International Conference on Humanoid Robots" Dec 7-10, 2009.; Chapter five is based on published work: -- Wettels, N., Parnandi, A.R., Moon, J.-H., Loeb, G.E. and Sukhatme, G.S. Grip control using biomimetic tactile sensing systems. IEEE/ASME Trans. Mechatronics, 14(6):718-723, 2009.; Chapter six is based on work that is unpublished and published; select material to be submitted to: International Journal of Robotics Research: -- Lin, C.H., Erickson, T.W., Fishel, J.A., Wettels, N., and Loeb, G.E. “Signal Processing and Fabrication of a Biomimetic Tactile Sensor Array with Thermal, Force and Microvibration Modalities” IEEE Int'l Conference Robotics & Biomimetics, Gulin, China, 2009. |
| Keyword | dexterous manipulation; feature extraction; force sensing; grasping; haptics; tactile sensing |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m3924 |
| Rights | Wettels, Nicholas B. |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Wettels-4272 |
| Archival file | uscthesesreloadpub_Volume44/etd-Wettels-4272.pdf |
Description
| Title | Page 1 |
| Full text | BIOMIMETIC TACTILE SENSOR FOR OBJECT IDENTIFICATION AND GRASP CONTROL by Nicholas B. Wettels A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (BIOMEDICAL ENGINEERING) May 2011 Copyright 2011 Nicholas B. Wettels |
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