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Description
To achieve the ambitious long-term goal of a feet of cooperating Flexible Autonomous

Machines operating in an uncertain Environment (FAME), this thesis addresses several

critical modeling, design, control objectives for rear-wheel drive ground vehicles.

Toward this ambitious goal, several critical objectives are addressed. One central objective of the thesis was to show how

To achieve the ambitious long-term goal of a feet of cooperating Flexible Autonomous

Machines operating in an uncertain Environment (FAME), this thesis addresses several

critical modeling, design, control objectives for rear-wheel drive ground vehicles.

Toward this ambitious goal, several critical objectives are addressed. One central objective of the thesis was to show how to build low-cost multi-capability robot platform

that can be used for conducting FAME research.

A TFC-KIT car chassis was augmented to provide a suite of substantive capabilities.

The augmented vehicle (FreeSLAM Robot) costs less than $500 but offers the capability

of commercially available vehicles costing over $2000.

All demonstrations presented involve rear-wheel drive FreeSLAM robot. The following

summarizes the key hardware demonstrations presented and analyzed:

(1)Cruise (v, ) control along a line,

(2) Cruise (v, ) control along a curve,

(3) Planar (x, y) Cartesian Stabilization for rear wheel drive vehicle,

(4) Finish the track with camera pan tilt structure in minimum time,

(5) Finish the track without camera pan tilt structure in minimum time,

(6) Vision based tracking performance with different cruise speed vx,

(7) Vision based tracking performance with different camera fixed look-ahead distance L,

(8) Vision based tracking performance with different delay Td from vision subsystem,

(9) Manually remote controlled robot to perform indoor SLAM,

(10) Autonomously line guided robot to perform indoor SLAM.

For most cases, hardware data is compared with, and corroborated by, model based

simulation data. In short, the thesis uses low-cost self-designed rear-wheel

drive robot to demonstrate many capabilities that are critical in order to reach the

longer-term FAME goal.
ContributorsLu, Xianglong (Author) / Rodriguez, Armando Antonio (Thesis advisor) / Berman, Spring (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Toward the ambitious long-term goal of a fleet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this thesis addresses several

critical modeling, design and control objectives for ground vehicles. One central objective was to show how off-the-shelf (low-cost) remote-control (RC) “toy” vehicles can be converted into intelligent multi-capability

Toward the ambitious long-term goal of a fleet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this thesis addresses several

critical modeling, design and control objectives for ground vehicles. One central objective was to show how off-the-shelf (low-cost) remote-control (RC) “toy” vehicles can be converted into intelligent multi-capability robotic-platforms for conducting FAME research. This is shown for two vehicle classes: (1) six differential-drive (DD) RC vehicles called Thunder Tumbler (DDTT) and (2) one rear-wheel drive (RWD) RC car called Ford F-150 (1:14 scale). Each DDTT-vehicle was augmented to provide a substantive suite of capabilities as summarized below (It should be noted, however, that only one DDTT-vehicle was augmented with an inertial measurement unit (IMU) and 2.4 GHz RC capability): (1) magnetic wheel-encoders/IMU for(dead-reckoning-based) inner-loop speed-control and outer-loop position-directional-control, (2) Arduino Uno microcontroller-board for encoder-based inner-loop speed-control and encoder-IMU-ultrasound-based outer-loop cruise-position-directional-separation-control, (3) Arduino motor-shield for inner-loop motor-speed-control, (4)Raspberry Pi II computer-board for demanding outer-loop vision-based cruise- position-directional-control, (5) Raspberry Pi 5MP camera for outer-loop cruise-position-directional-control (exploiting WiFi to send video back to laptop), (6) forward-pointing ultrasonic distance/rangefinder sensor for outer-loop separation-control, and (7) 2.4 GHz spread-spectrum RC capability to replace original 27/49 MHz RC. Each “enhanced”/ augmented DDTT-vehicle costs less than 􀀀175 but offers the capability of commercially available vehicles costing over 􀀀500. Both the Arduino and Raspberry are low-cost, well-supported (software wise) and easy-to-use. For the vehicle classes considered (i.e. DD, RWD), both kinematic and dynamical (planar xy) models are examined. Suitable nonlinear/linear-models are used to develop inner/outer-loopcontrol laws.

All demonstrations presented involve enhanced DDTT-vehicles; one the F-150; one a quadrotor. The following summarizes key hardware demonstrations: (1) cruise-control along line, (2) position-control along line (3) position-control along curve (4) planar (xy) Cartesian stabilization, (5) cruise-control along jagged line/curve, (6) vehicle-target spacing-control, (7) multi-robot spacing-control along line/curve, (8) tracking slowly-moving remote-controlled quadrotor, (9) avoiding obstacle while moving toward target, (10) RC F-150 followed by DDTT-vehicle. Hardware data/video is compared with, and corroborated by, model-based simulations. In short, many capabilities that are critical for reaching the longer-term FAME goal are demonstrated.
ContributorsLin, Zhenyu (Author) / Rodriguez, Armando Antonio (Committee member) / Si, Jennie (Committee member) / Berman, Spring Melody (Committee member) / Arizona State University (Publisher)
Created2015