Mixed-Signal Sensing, Estimation, and Control for Miniature Robots

Simple item page
dc.contributor.advisorAbshire, Pamela Aen_US
dc.contributor.authorKuhlman, Michael Josephen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2013-07-04T05:30:09Z
dc.date.available2013-07-04T05:30:09Z
dc.date.issued2012en_US
dc.description.abstractControl of miniature mobile robots in unconstrained environments is an ongoing challenge. Miniature robots often exhibit nonlinear dynamics and obstacle avoidance introduces significant complexity in the control problem. In order to allow for coordinated movements, the robots must know their location relative to the other robots; this is challenging for very small robots operating under severe power and size constraints. This drastically reduces on-board digital processing power and suggests the need for a robust, compact distance sensor and a mixed-signal control system using Extended Kalman Filtering and Randomized Receding Horizon Control to support decentralized coordination of autonomous mini-robots. Error analysis of the sensor suggests that system clock timing jitter is the dominant contributor for sensor measurement uncertainty. Techniques for system identification of model parameters and the design of a mixed-signal computer for mobile robot position estimation are presented.en_US
dc.identifier.urihttp://hdl.handle.net/1903/14244
dc.subject.pqcontrolledElectrical engineeringen_US
dc.subject.pqcontrolledRoboticsen_US
dc.subject.pquncontrolledAnalog Computingen_US
dc.subject.pquncontrolledDistance Only Sensingen_US
dc.subject.pquncontrolledExtended Kalman Filteringen_US
dc.subject.pquncontrolledMiniature Roboticsen_US
dc.subject.pquncontrolledModel Predictive Controlen_US
dc.titleMixed-Signal Sensing, Estimation, and Control for Miniature Robotsen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Kuhlman_umd_0117N_13646.pdf
Size:
642.84 KB
Format:
Adobe Portable Document Format
Download

Collections

UMD Theses and Dissertations
Electrical & Computer Engineering Theses and Dissertations