[robotics-worldwide] [journals] Autonomous Robots - Special Issue on "Constrained decision making in robotics: models, algorithms, and applications"

Stefano Carpin scarpin at ucmerced.edu
Wed Jul 2 17:38:16 PDT 2014


The Autonomous Robots journal invites papers for a special issue 
on “Constrained decision-making in robotics: models, algorithms, 
and applications.” 

As the complexity of  robotic tasks grows, robotic decision makers 
increasingly face the problem  of trading off different objectives (for 
example, safety versus speed, or, in a reinforcement learning framework, 
balancing exploration versus exploitation for fast convergence). A natural 
framework for this class of problems is constrained decision-making, 
whereby a decision maker seeks to optimize a given cost function (often 
stochastic) while keeping other costs (usually involving risk assessments) 
below given bounds. Aspects of this framework have been addressed in 
isolation by the operations research and finance communities (for example, 
algorithms for constrained Markov decision processes and modeling of 
risk preferences), but the application of such a framework to the robotics 
domain is relatively new, fueled by application as diverse as safe 
autonomous driving, collision avoidance for unmanned aerial vehicles, 
and risk-aware learning for autonomous robots. 

Accordingly, this special issue aims at presenting the state of the art on 
the fast growing field of constrained decision-making in robotics. 
Specifically, it focuses on models, algorithms, and applications to solve 
constrained decision and planning problems for single and multiple 
robot systems. We invite submissions of original research papers addressing 
constrained decision making problems with an emphasis on theories and 
frameworks validated on robotic systems operating in the physical world. 

Topics of interest include, but are not limited to: 
 
- Modeling of constraints (in particular, risk) for robotic applications; 
- Algorithms for risk-aware decision making and learning for robotic systems, with a 
focus on online computation; 
- Chance-constrained robotic motion planning; 
- Hierarchical constrained decision making; 
- Applications of Constrained MDPs and Constrained POMDPs to robot planning; 
- Applications: ground, underwater, aerial, and space robots; 
- Benchmarks and performance metrics for constrained decision-making problems; 
- Verification and validation techniques for constrained decision-making problems. 

Guest editors:
Stefano Carpin, University of California, Merced
Marco Pavone, Stanford University

CFP: http://static.springer.com/sgw/documents/1459402/application/pdf/CFP+Constrained+decision-making+-+deadline+10-15-2014.pdf

Important dates:
October 15, 2014: Submission deadline
January 15, 2015: First reviews completed
February 15, 2015: Revised papers due
March 30, 2015: Final decision

Manuscript must be submitted to http://AURO.edmgr.com.


Stefano Carpin, PhD 
Associate Professor 
School of Engineering 
University of California, Merced 
http://faculty.ucmerced.edu/scarpin 
http://robotics.ucmerced.edu 



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