Dissertation/Thesis Abstract

Mixed-Signal Sensing, Estimation and Control for Miniature Robots
by Kuhlman, Michael Joseph, M.S., University of Maryland, College Park, 2012, 131; 1541601
Abstract (Summary)

Control 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.

Indexing (document details)
Advisor: Abshire, Pamela A.
Commitee: Bergbreiter, Sarah, Horiuchi, Timothy, Krishnaprasad, P. S., Martins, Nuno
School: University of Maryland, College Park
Department: Electrical Engineering
School Location: United States -- Maryland
Source: MAI 52/01M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Electrical engineering, Robotics
Keywords: Analog computing, Distance only sensing, Extended kalman filtering, Miniature robotics, Model predictive control
Publication Number: 1541601
ISBN: 9781303245220