[robotics-worldwide] Postdoc position Autonomous Systems MBARI, California

Kanna Rajan Kanna.Rajan at mbari.org
Sun Nov 30 11:53:22 PST 2008


[apologies for multiple messages]

The Autonomous System group at the Monterey Bay Aquarium Research  
Institute (MBARI) invites applications for 1 two-year postdoc position.

MBARI (http://www.mbari.org)  is a private non-profit Oceanographic  
research institute located in Moss Landing, California, in the heart  
of the  largest marine sanctuary in the United States, just outside  
Silicon Valley. The institute is an inter-disciplinary research  
institution guided by a strong peer relationship between scientists,  
engineers and marine operations staff. MBARI pioneered the use of  
Remotely Operated Vehicles (ROVs http://www.mbari.org/dmo/vessels_vehicles/tiburon/tiburon.html) 
  and Autonomous Underwater Vehicles (AUVshttp://www.mbari.org/auv/default.htm) 
  for deep ocean research and continues to be at the cutting edge of  
marine robotics, marine sensor development, ocean chemistry, marine  
geology, micro-biology and ecology.

Research Focus:

The Autonomous Systems group is uniquely placed as being the only  
Artificial Intelligence group within an operational oceanographic  
setting anywhere. The focus of the groups effort is in automated  
reasoning for embodied robust intelligence for AUVs with a focus on  
Automated Planning, Execution, Constraint-Based Reasoning and Machine  
Learning. The core development effort is to enable adaptive control  
for AUVs to survey, sample and characterize dynamic and episodic ocean  
phenomenon such as Harmful Algal Blooms, Fronts and Thin Layers which  
have substantial societal impact (http://www.mbari.org/autonomy/ 
TREX/). Further efforts are underway to study the feasibility of goal- 
based commanding for underwater feature-based SLAM, mixed-initiative  
platform control and multi-vehicle coordination.

Research Environment:

The Autonomous Systems group was established in 2005 by researchers  
from NASA with extensive background in commanding spacecraft including  
the twin Mars Rovers Spirit and Opportunity. A strong inter- 
disciplinary effort with biological oceanographers at MBARI and others  
outside has driven the design and deployment of a hybrid executive*  
which enables an AUV to adaptively sample the environment using  
Planning and Machine Learning techniques to inform dynamic in-situ  
behavior. Publishing in peer-reviewed conferences and journals in AI,  
Robotics and the Ocean Sciences and interacting with scientists in the  
fields of biology, chemistry, ecology, genetics, ocean physics, marine  
robotics is an important aspect of the research effort. The group  
collaborates with AI and Robotics researchers in academia in the US  
and Europe and hosts visiting graduate students and researchers from  
within the US and Europe.

Key topic areas of interest for this position are:

1. Automated Planning and Execution
2. Scheduling
3. Machine Learning
4. Constraint-based Reasoning
5. Distributed Planning

Applicants are encouraged to communicate with the PI for project  
feasibility and relevance to ongoing MBARI research. Women and  
minorities are strongly encouraged to apply. Details of the  
application process are at http://www.mbari.org/oed/jobs/Postdocs-2009.html 
. The deadline for applications is December 11th 2008.


*
1.	McGann, C., Py, F., Rajan, K., Ryan, J., Thomas, H., Henthorn, R.,  
and McEwen, R. “Preliminary Results for Model-Based Adaptive Control  
of an Autonomous Underwater Vehicle” Intnl. Symposium on Experimental  
Robotics (ISER) (Athens, Greece, 2008).

2.	McGann, C., Py, F., Rajan, K., Ryan, J., and Henthorn, R.  
“Adaptive Control for Autonomous Underwater Vehicles” In Proc.  
Assoc. for the Advancement of Artificial Intelligence, National  
Conference (AAAI) (Chicago, IL, 2008).

3.	McGann, C., Py, F., Rajan, K., Thomas, H., Henthorn, R., and  
McEwen, R. “A Deliberative Architecture for AUV Control” In Proc.  
IEEE International Conference on Robotics and Automation (ICRA)  
(Pasadena, CA, May 2008).

4.	McGann, C., Py, F., Rajan, K., Thomas, H., Henthorn, R., and  
McEwen, R., “Automated Decision Making For a New Class of AUV  
Science”, In ASLO/Ocean Sciences, Florida, 2008.

5.	Py, F., Ryan, J., Rajan, K., McGann, C., Fox, M, “Adaptive Water  
Sampling from an Autonomous Underwater Vehicle based on Unsupervised  
Clustering”, In ASLO/Ocean Sciences, Florida, 2008

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