Workshop on Informative Path Planning and Adaptive Sampling

Title: Workshop on Informative Path Planning and Adaptive Sampling
When&where: May 21 or 25, ICRA2018, Brisbane, Australia

Robots rely on models of themselves and the environment to understand
and act in the world around them. In many cases, these models are
trained on observed (sampled) data, and the goal is to collect the set
of data that will generate the most useful model within the resource
constraints of the operating robot system. This process is known as
adaptive informative sampling, and is applicable to a wide range of
robotic applications, from modeling environmental phenomena to
approximating value functions in reinforcement learning. However,
despite the prevalence of adaptive sampling methods in
state-of-the-art robotic applications, there are still many
challenging and open problems. For example, how should we estimate the
utility of future samples, or design information sharing protocols for
a multi-robot team such that they can effectively reason over their
joint sampling action?

The main goal of this workshop is to discuss and share ideas related
to informative path planning and adaptive sampling. This is a topic
that spans all robotic domains and we want to bring together
researchers from all fields—marine, ground and aerial robotics, as
well as the multi-agent and learning communities—who might otherwise
not be aware of the valuable techniques being developed in each of
these domains, and the correspondence between their research. This
workshop will look at the various aspects of informative path
planning, including, but not limited to, its theoretical foundations,
active sampling, spatio-temporal variability, and multi-robot
planning. One of the aims of this workshop is to generate candid
discussion on how these theoretical components interact with real
world robotic constraints such as imperfect sensing and resource
limitations. To that end, we also invite talks from potential
end-users; e.g. oceanographers, agriculturists, meteorologists.

Topics of interest include:
* Theoretical foundations of informative path planning and adaptive sampling
* Exploration, mapping, surveillance, and inspection missions in
unknown or dynamic environments
* Persistent environmental monitoring, particularly methods for
handling spatial and/or temporal variability
* Information sharing and data fusion for multi-robot teams
* Coordination algorithms for multi-robot missions
* Handling real robot constraints, such as large volumes of data or
communication constraints
* Budgeted sampling under resource limitations
* Employing these methods in practice for real-world applications

* Stephanie Kemna (POC), University of Southern California, USA
* Jen Jen Chung, Oregon State University, USA
* Nicholas Lawrance, Oregon State University, USA
* Graeme Best, University of Sydney, Australia

Date of the event: 
Monday, 21 May, 2018 - 00:00 to Friday, 25 May, 2018 - 00:00
Conference Name: 
ICRA2018, Brisbane, Australia