- Brooks, Rodney. "Achieving Artificial Intelligence through Building
Robots." Boston: Massachusetts Institute of Technology, 1986.
- Rodney Brooks warns that abstraction can be dangerous and that truly
intelligent robotic systems will not follow the box world we have created for
them. Therefore, we should not design our robot with limited conceptions of
its world, but instead create the desired complex behavior by combining simple
behaviors. Unfortunately, our robots are not of the right architecture to
create "robotic insects," but in some cases using a subsumption architecture
may be appropriate.
- Horswill, Ian. "The Polly System." AI and Mobile Robots.
- The Polly system has some similarities to our own robot in that both are
intended to use vision to perform tasks for extended periods of time. Both
robots also try to find humans. The Polly system uses place recognition that
is different to ours. Polly is sensitive to dynamic changes in the environment,
while our system relies on navigating by fixed landmarks such as doors and
- Vaughan, R. N. Sumpter, A. Frost, and S. Cameron. "Experiments in
Automatic Flock Control." Edinburgh, UK, 1998.
- This look at robot-animal interaction, while interesting, was also very
simple. Our experiment will be involving humans, which, unfortunately, don't
exhibit flock behavior. At least, they don't usually. Additionally, the
experiment "cheated" in that an overhead camera was used to help coordinate the
positions of the actors (the robot and the ducks) instead of using only
sensors on the robot itself. We will not have this option for our experiment
and so very little of this experiment usefully applies to our experiment.
- Mark Yim, David G. Duff, and Kimon D. Roufas. "PolyBot: a Modular
Reconfigurable Robot." IEEE International Conference on Robotics & Automation.
- While fascinating in and of itself, PolyBot holds very little relevance to
our project. The paper is on building modular reconfigurable robots, a type of
robot architecture that our robot is not.
- Martin, Martin C. and Hans Moravec. "Robot Evidence Grids." CMU RI TR
- Robot evidence grids provide an algorithm by which to map the robot's
environment. Given sufficient time to explore, they can provide accurate
mappings of obstacles, even from low quality sensors. Since it is likely we
will also be using low quality sensors, we may consider implementing this
algorithm into our robot's "brain."
- Moravec, Hans. "Robots, After All." Communications of the ACM. October
2003. Vol. 46, No. 10.
- This paper contains very little implementation level details of robotics,
but instead steps back to give a broad view of what the future may hold. The
paper holds very little application to our project specifically, but may be
applicable to us over time and as we look for changes in robotic technology
over the next several years.
- Illah Nourbakhsh, Rob Powers, and Stan Birchfield. "DERVISH: An
Office-Navigating Robot." Copyright 1995, AAAI.
- Use of modules, percept pair, simulators are not sufficient, "a highly
detailed model of reality is doomed because of enormous computational
complexity", state-set representation, interleave planning and execution, must
- Dieter Fox, Wolfram Burgard, Frank Dellaert, and Sebastian Thrun. "Monte
Carlo Localization: Efficient Position Estimation for Mobile Robots."
Copyright 1999, AAAI.
- We are using Monte Carlo Localization (MCL) on our Evolution to
efficiently and effectively map it's position within the Libra Complex (we
already have a map).
- Thrun, Sebastian. "Robotic Mapping: A Survey." CMU-CS-02-111, February
- (Insert applications comments here)
- R. Grabowski, L. Navarro-Serment, and P. Khosla. "An Army of Small
Robots." SciAm Online May 2004.
- While interesting, this article had very little relevance to our project.
We are working with the relatively large Evolution platform, not a several
centimeter "mini". Also, we only have one robot, so group mapping/localization
techniques and such do not apply. Neat ideas, but not directly applicable.
Also, with a title including both the words "Army" and "Robots", the
lack of an in-depth discussion of equipping rocket launchers is simply
- Toyama, Kentaro and Gregory Hager. "If at First You Don't Succeed..."
Copyright 1997, AAAI.
- Naturally, our Big Brother Bot program will incorporte some degree of
Anti-failure robustness. Post-failure robustness, however, will also be
crucial. There are two primary cases where post-failure recovery is not only
possible, but expected by any reasonable tracking robot. The first is if the
robot gets lost (e.g. the kidnapping problem). To handle this, we are using
MCL which naturally incorporates a degree of post-failure robustness because
it can address both the kidnapping and the localization problem at the same
time and by using very similar methods. The other major failure will be losing
track of the target BBB was tracking. For this situation, we will probably use
a simpler version of Toyoma and Hager's Incremental Focus of Attention (IFA)
framework. We will first try to re-find the target using the camera, but if
that fails, the robot will resort to its wandering algorithm looking for
another target. This is a form of post-failure recovery.
- LaValle, Steven and James Kuffner. "RRT-Connect: An Efficient Approach to
Single-Query Path Planning." Copyright 2000, ICRA.
- While the RRT-Connect is a fascinating and attractive path-planning
algorithm, our sentinel robot did not use path planning. If an obstacle comes
between it and its prey, it merely stops. A possible enhancement to our robot
would be to add a complex path-planning algorithm, such as RRT-Connect, thereby
enabling the robot to pursue and destroy its target more easily.