DocumentCode :
1365034
Title :
Developing a Stochastic Dynamic Programming Framework for Optical Tweezer-Based Automated Particle Transport Operations
Author :
Banerjee, Ashis Gopal ; Pomerance, Andrew ; Losert, Wolfgang ; Gupta, Satyandra K.
Author_Institution :
Dept. of Mech. Eng., Univ. of Maryland, College Park, MD, USA
Volume :
7
Issue :
2
fYear :
2010
fDate :
4/1/2010 12:00:00 AM
Firstpage :
218
Lastpage :
227
Abstract :
Automated particle transport using optical tweezers requires the use of motion planning to move the particle while avoiding collisions with randomly moving obstacles. This paper describes a stochastic dynamic programming based motion planning framework developed by modifying the discrete version of an infinite-horizon partially observable Markov decision process algorithm. Sample trajectories generated by this algorithm are presented to highlight effectiveness in crowded scenes and flexibility. The algorithm is tested using silica beads in a holographic tweezer set-up and data obtained from the physical experiments are reported to validate various aspects of the planning simulation framework. This framework is then used to evaluate the performance of the algorithm under a variety of operating conditions.
Keywords :
Markov processes; holography; radiation pressure; stochastic programming; holographic tweezer set-up; infinite-horizon partially observable Markov decision process algorithm; motion planning framework; optical tweezer-based automated particle transport operations; optical tweezers; silica beads; stochastic dynamic programming framework; Automated planning; microsphere; optical tweezer (OT); partially observable Markov decision process; simulation; stochastic dynamic programming;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2009.2026056
Filename :
5233768
Link To Document :
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