19,855 research outputs found
Assistive Planning in Complex, Dynamic Environments: a Probabilistic Approach
We explore the probabilistic foundations of shared control in complex dynamic
environments. In order to do this, we formulate shared control as a random
process and describe the joint distribution that governs its behavior. For
tractability, we model the relationships between the operator, autonomy, and
crowd as an undirected graphical model. Further, we introduce an interaction
function between the operator and the robot, that we call "agreeability"; in
combination with the methods developed in~\cite{trautman-ijrr-2015}, we extend
a cooperative collision avoidance autonomy to shared control. We therefore
quantify the notion of simultaneously optimizing over agreeability (between the
operator and autonomy), and safety and efficiency in crowded environments. We
show that for a particular form of interaction function between the autonomy
and the operator, linear blending is recovered exactly. Additionally, to
recover linear blending, unimodal restrictions must be placed on the models
describing the operator and the autonomy. In turn, these restrictions raise
questions about the flexibility and applicability of the linear blending
framework. Additionally, we present an extension of linear blending called
"operator biased linear trajectory blending" (which formalizes some recent
approaches in linear blending such as~\cite{dragan-ijrr-2013}) and show that
not only is this also a restrictive special case of our probabilistic approach,
but more importantly, is statistically unsound, and thus, mathematically,
unsuitable for implementation. Instead, we suggest a statistically principled
approach that guarantees data is used in a consistent manner, and show how this
alternative approach converges to the full probabilistic framework. We conclude
by proving that, in general, linear blending is suboptimal with respect to the
joint metric of agreeability, safety, and efficiency
A Wikipedia Literature Review
This paper was originally designed as a literature review for a doctoral
dissertation focusing on Wikipedia. This exposition gives the structure of
Wikipedia and the latest trends in Wikipedia research
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