The combination of SRI's fuzzy control, local perceptual
space, and procedural reasoning technologies
provides for flexible, robust control of an autonomous vehicle operating
within an (unmodified) office environment. Purposeful behaviors (e.g.,
going to a specific location) are dynamically blended with reactive
behaviors (e.g., avoideing a moving obstacle) to provide smooth and
compliant control of the vehicle as it navigates according to a strategic
SRI's work in combining sensory information with map-based information has
led to the development of the local perceptual space
(LPS), an egocentric view of local space where information from
all sensors and interpretation routines is posted. Here, information from
different sensor modalities, and different levels of abstraction and
complexity, freely mixes. As new information is posted, different routines
respond by processing it and posting new results; this hierarchical nature
of interpretation allows time-critical routines to respond quickly, while
more complex routines take more time.
The LPS is used as the repository for the results from a collection of
interpretation routines on the robot. This includes raw distance readings,
extracted surfaces (e.g., walls, obstacles), objects from the map (e.g.,
specific corridors), and abstract control points from the strategic plan
(e.g., positions to obtain).
At any time, several active behaviors are responding to the information in
the LPS. Some of these are purposeful (e.g., following a corridor to reach a
target location), while others are for contingencies (e.g., avoiding
obstacles). Each behavior is defined by a set of fuzzy rules. A rule's level of
activation corresponds to the degree that its precondition matches the LPS; when
the precondition of a rule holds, then its action is very desirable; when the
precondition partially matches, the action is less desirable. By blending the actions of all the rules, in the
currently active behaviors, according to their levels of activation, an
"optimal" action is derived. Since the conditions in the environment typically
change slowly, the repeated application of the same fuzzy rules smoothly blends
actions over time. For example, as a person approaches, the robot gradually
veers away, and then returns to its original course once the person has passed.
At a higher level, PRS-Lite, a version of SRI's PRS-CL with a 100 milliseconds cycle time, provides
real-time supervisory control for the robot. It does so by following a
strategic plan that states the sequence of goals that the robot needs to
satisfy. This plan may have been automatically produced by a generative
planner or directly specified by the user. PRS-Lite utilizes a library of
predefined procedures to reduce these high-level goals into subsequences of
lower-level goals; at the lowest level, goals are satisfied by activating
and deactivating behaviors according to the refined plan and the
situation-dependent information in the LPS.
Our in-house experiments have shown that this methodology leads to robust,
flexible controllers that reliably attain user-specified goals while
smoothly reacting to unexpected events. Flakey freely roams our offices,
coexisting with our staff. Its presence is nonthreatening, and it requires
no special accommodations by those around it. The utility of this
architecture was apparent in the first two AAAI mobile robot competitions.
In the first (1992), Flakey was the only entry capable of successfully
performing in the object location and mapping event without requiring
environmental modifications. Flakey's multimodal sensor interpretation
proved to be very effective, with the sonar routines suggesting candidate
objects that were verified by the structured light routines. Flakey
received special recognition for its smooth and compliant behavior in the
presence of people as exemplified by one judge's comment: ``Only robot I
felt I could sit or lie in front of.'' In the 1993 contest, additional
visual recognition of landmarks and visual stereo processing for obstacles
were incorporated. Flakey finished in the top category in the two events it
Karen L. Myers,
Enrique H. Ruspini,
Artificial Intelligence Center
PRS-CL and PRS-Lite are trademarks of SRI International.
Copyright © 1995 SRI International, 333 Ravenswood Ave., Menlo Park, CA 94025 USA.
All rights reserved.