Detailed Research Interests
I am interested in building robots and related systems that are cost-effective in today's marketplace. It is clear that
sensing and cognition have a long way to go before an autonomous system can match the ability of even a small
child. Yet, it is also clear that autonomous systems have a place in our world now if they can compete with humans
because they are better, faster, cheaper, safer or even more entertaining.
I am also interested in the study of
the mobile robot as a wholistic system. Aspects of that study include the
interrelationships of subsystem and system level requirements (constraints),
the development of performance models (objectives), and highly principled and
well-argued approaches to the construction of the best achievable solution. I want to understand what works well and
why so that I can profitably manipulate the governing relationships in order to
do even better.
Some recent area os research include:
Off-Road Mobility
The goal of this work is to improve the performance and reliability of
vehicles that drive themselves outdoors, off the road. I am interested
in the systems aspects of constructing high-performance autonomous
vehicles.
Vision-Based Localization
There are basically two methods of position estimation: deduced
reckoning and triangulation.. Triangulation methods are those which
associate measurements gathered on the vehicle with some prestored map
of the area to produce a "fix" on the position of the vehicle. Systems
based only on deduced reckoning get more and more lost over time, so
some form of triangulation is almost always necessary in practice - if
accurate absolute positioning is desired.
I have developed a visual guidance system for factory robots which uses
only cameras (vision) and odometry sensing (wheel rotations). It uses
no infrastructure such as laser retroreflectors or wires or magnets
embedded in the floor. It relies only on the naturally occuring texture
on the floor. This system is an existence proof that competent and
reliable robot localization can be accomplished with nothing but vision
and the odometry sensing available on any mobile robot. Coincidentally,
the image processing involved is a 2D analog of the Global Positioning
Satellite navigation system (GPS).
There are many ways in which this principle can be used in different
ways and in different environments including the outdoors. I would like
to extend this work to having ground vehicles navigate from overhead
imagery and bulding autonomous vehicle convoys based on nothing but
vision.
High Speed Motion Planning & Control
While much is known about how to handle the problem of motion
planning in general, relatively little work has been done on the
problem of planning robot motions using highly complex models in
difficult environments or planning at such high speeds that a good
decision must be made in a very small fraction of a second. I am
interested in addressing these challenges in both practice and in
theory. Of late, I have been working on effective path sampling strategies for high speed and complex environments.
Alonzo Kelly
<alonzo@cmu.edu>
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