[robotics-worldwide] ACC Workshop: DM Algorithms for UVs

Krishna Kalyanam krishna.kalyanam at gmail.com
Thu Apr 11 06:15:12 PDT 2013


 *Decision Making Algorithms for Unmanned Vehicles*
Organizers: Sivakumar Rathinam, Krishnamoorthy Kalyanam, Swaroop Darbha
Venue: American Control Conference, Washington DC, June 16, 2013
Speakers from Air Force Research Lab: Dr. Meir Pachter, Dr. Krishnamoorthy
Kalyanam
Speaker from University of Florida: Dr. Pramod Khargonekhar
Speakers from Texas A & M University: Dr. Sivakumar Rathinam and Dr.
Swaroop Darbha

This workshop is focused on disseminating recent advances in the area of
decision making algorithms for Unmanned Vehicles (UVs). Small autonomous
UVs are seen as ideal platforms for many military applications such as
monitoring targets, mapping a given area, aerial/road surveillance and
civil applications such as search and rescue missions, reconnaissance, fire
monitoring etc. The main advantage of using these vehicles is that they can
be used in situations where a manned mission is dangerous and/or is not
possible. Even though there are several advantages in using small UVs,
these vehicles have resource constraints due to their limited computational
and sensing capabilities. To successfully realize a mission involving UVs,
one has to optimally use the available resources often in the presence of
uncertainty, motion and sensing constraints, and possibly adversarial
action. This workshop brings together practitioners from the academia and
the Air Force Research Lab (AFRL), to provide a complete picture of the
challenges behind UVs mission planning, specification, scheduling and
real-time optimization. The talks in this workshop will discuss open
problems, touch upon various issues in the area of UV decision making,
provide practical solutions for some of the underlying problems and also
illustrate the theoretical background behind the techniques. In particular,
the talks will focus on the following topics:

   1. An overview of UV decision making problems under uncertainty
   2. Constrained motion planning algorithms for a collection of UVs
   3. Approximation algorithms for UVs with resource and motion constraints
   4. Role of information in dynamic games involving UVs and adversaries
   5. Approximate linear programming methods for stochastic dynamic
   programs and its application to UVs
   6. Intruder isolation and capture on a road network using partial and
   delayed information


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