ULTRASONIC IMAGING AND TACTILE SENSING FOR ROBOTIC SYSTEMS

Balasubramanian, Aravind Baradhwaj

Title:

ULTRASONIC IMAGING AND TACTILE SENSING FOR ROBOTIC SYSTEMS

dc.contributor.advisor	Taylor, David G.
dc.contributor.author	Balasubramanian, Aravind Baradhwaj
dc.contributor.committeeMember	Durgin, Gregory D
dc.contributor.committeeMember	Wardi, Yorai
dc.contributor.committeeMember	Zhang, Ying
dc.contributor.committeeMember	Ferri, Aldo A
dc.contributor.department	Electrical and Computer Engineering
dc.date.accessioned	2022-08-25T13:35:11Z
dc.date.available	2022-08-25T13:35:11Z
dc.date.created	2022-08
dc.date.issued	2022-07-13
dc.date.submitted	August 2022
dc.date.updated	2022-08-25T13:35:11Z
dc.description.abstract	This research develops several novel algorithms that enhance the operation of ultrasonic and tactile sensors for robotic applications. The emphasis is on reducing the overall cost, system complexity, and enabling operation on resource-constrained embedded devices with the main focus on ultrasonics. The research improves key performance characteristics of pulse-echo sensor systems -- the minimum range, range resolution, and multi-object localization. The former two aspects are improved through the application of model-based and model-free techniques. Time optimal principles precisely control the oscillations of transmitting and receiving ultrasonic transducers, influencing the shape of the pressure waves. The model-free approach develops simple learning procedures to manipulate transducer oscillations, resulting in algorithms that are insensitive to parameter variations. Multi-object localization is achieved through phased array techniques that determine the positions of reflectors in 3-D space using a receiver array consisting of a small number of elements. The array design and the processing algorithm allow simultaneous determination of the reflector positions, achieving high sensor throughputs. Tactile sensing is a minor focus of this research that leverages machine learning in combination with an exploratory procedure to estimate the unknown stiffness of a grasped object. Gripper mechanisms with full-actuation and under-actuation are studied, and the object stiffness is estimated using regression. Sensor measurements use actuator position and current as the inputs. Regressor design, dataset generation, and the estimation performance under nonlinear effects, such as dry friction, parameter variations, and under-actuated transmission mechanisms are addressed.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/67243
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	damping
dc.subject	gripper
dc.subject	minimum range
dc.subject	range resolution
dc.subject	ringing cancellation
dc.subject	stiffness
dc.subject	ultrasonic
dc.subject	vibration control
dc.subject	3-D sensing
dc.title	ULTRASONIC IMAGING AND TACTILE SENSING FOR ROBOTIC SYSTEMS
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	Taylor, David G.
local.contributor.corporatename	School of Electrical and Computer Engineering
local.contributor.corporatename	College of Engineering
relation.isAdvisorOfPublication	a6615de9-0526-43fd-84a6-b2185a733191
relation.isOrgUnitOfPublication	5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level	Doctoral