Abstract
Motivation and Objectives
Topics
Speakers
Workshop Program |
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.
[Back to top]
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
[Back to top]
Speakers
| H. Harry Asada |
M.I.T. |
|
| Vijay Kumar |
University of Pennsylvania |
|
| Yoshihiko Nakamura |
University of Tokyo |
|
| Daniela Rus |
M.I.T. |
|
| Metin Sitti |
Carnegie Mellon Univ. |
|
| Russell Tedrake |
M.I.T. |
|
| Auke Ijspeert |
Swiss Federal Institute of Technology at Lausanne |
|
| Sebastian Thrun |
Stanford University |
|
| George Pappas |
University of Pennsylvania |
|
| John Leonard |
M.I.T. |
|
[Back to top]
Workshop Program
9:00 am Welcome and opening remarks
9:15 am Vijay Kumar University of Pennsylvania
9:45 am Metin Sitti Carnegie Mellon Univ.
10:15 am Break
10:30 am Harry Asada M.I.T.
11:00 am (TBA, Pappas, Fukuda, or Dario)
11:30 am Interim Discussion
12:00 noon Lunch
1:00 pm Sebastian Thrun Stanford University
1:30 pm Russell Tedrake M.I.T.
2:00 pm Auke Ijspeert, SFITL
2:30 pm Break
2:45 pm Daniela Rus M.I.T.
3:15 pm Yoshihiko Nakamura University of Tokyo
3:45 pm (TBA, Faugeras, Burdick, or Leonard)
4:15 pm Final Discussion
5:00 pm Closing remarks
[Back to top]
|
