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[交流] 【2009-05-12】Stochasticity in Robotics and Biological Systems

Workshop Web Site:

http://web.mit.edu/asada/www/icra2009/icra_stochasticWS.html


*Speakers:*

Vijay Kumar University of Pennsylvania

Yoshihiko Nakamura University of Tokyo

Daniela Rus M.I.T.

Metin Sitti Carnegie Mellon Univ.

Auke Ijspeert Swiss Federal Institute of Technology at Lausanne

Franz Hover M.I.T.

George Pappas University of Pennsylvania

H. Harry Asada M.I.T.

*Abstract:*

The workshop, ?Stochasticity in Robotics and Biological Systems?, is a
unique workshop; while addressing diverse topics of robotics we focus on
an underpinning discipline and theory across many branches of robotics.
Stochasticity has been a central issue in diverse robotics problems;
Modeling of uncertain environment, estimation of state and parameters
from noisy data, and decision making based on partial or incomplete
information are all critical issues in SLAM, swarm robots, task
planning, machine learning, neuro-robotics, and human intension
understanding. Stochasticity is also a crucial aspect in biological
systems where the multitude of cells and molecules interact
stochastically. Yet, collective behaviors of those agents are well
regulated and even robust and versatile. Recent progress in systems
biology has revealed that the stochastic nature of cell behaviors and
random molecular dynamics are the key to the understanding of their
collective behaviors and regulatory mechanisms. Researchers of swarm
robotics and others are learning from biological systems new stochastic
regulatory mechanisms and protocols. Thus stochasticity is heavily
involved in diverse fields of robotics and biological systems. The
objective of this workshop is to bring together leaders in these
isolated research areas, address fundamental issues across the diverse
topics, and establish a scientific and disciplinary foundation of
robotics. We think that considering fundamental issues beyond specific
problems in hand is an important exercise, which will facilitate
interdisciplinary studies and will lead to discoveries and breakthroughs
for the future.

*Motivation and Objectives:*

Stochasticity has been playing a central role in many branches of
robotics research. Not only basic signal processing, communication,
filtering, and control, but also advanced localization, identification,
and planning as well as learning and optimization are all heavily
involved in stochasticity. Understanding of the stochastic nature of
robotic systems and its strategic use are integral part in developing
effective systems. The robotics community has been exploring advanced
use of stochasticity for system architecture, algorithm development, and
communication and control design. Stochasticity is one of the key
disciplines that underpin robotics.

Biological systems are essentially noisy systems, built upon
thermodynamic random processes. Yet, a biological system is a highly
regulated system that is robust and sustainable as well as flexible and
adaptable. Although individual cell behaviors are stochastic, once
assembled, populations of the cells exhibit a particular morphological
structure and develop high-level functionality. There must be effective
architecture and regulatory mechanisms exploiting stochasticity that
today?s engineered systems have not yet utilized. It will be an exciting
scientific adventure as well as an ambitious engineering challenge to
explore a biological approach to treating and utilizing stochasticity
and apply it to robotics and general engineered systems.

The objectives of this workshop are to bring together researchers from
diverse fields of robotics and biological systems, display the state of
the art, explore emerging new theory and methodologies, and chart new
directions of robotics. Stochasticity can be used effectively for better
estimating, exploring, and optimizing the system as well as for
strategically organizing and constructing robotic systems. In
traditional engineered systems, randomness has been treated as an
unwanted property that should be filtered out. In contrast, the goal of
emerging new directions is to seek ways of exploiting and utilizing
stochasticity, as observed in biological systems. The overarching aim of
this workshop is to put in perspective the diverse research activities
in the broad cross-disciplinary areas of robotics, cell biology,
neuroscience, and control, and explore new methodologies and
applications, which will be enabled by addressing stochasticity from a
broad system viewpoint.

*List of Topics:*

Specific topics of invited talks will include:

- SLAM and integrated model building, data acquisition, and decision
processes

- Complex system identification, including human behavior and intension
estimation

- Swarm robot control and emergent behaviors of multi-robot systems

- Machine learning, stochastic approximation, and stochastic planning
and optimization

- Neural system modeling, signal processing, and inference.

- Emergent behaviors of cell populations and systems biology

- Bacteria behavior modeling and control

- Self-assembly and chemical kinetics in micro/nano systems

[ Last edited by 努力着 on 2009-2-27 at 13:37 ]
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