SW-4-4-2: Multi-Particle Path Planning using Optical Tweezers

Dr. Ashish Banerjee, M.I.T, USA,

Prof. Satyandra K. Gupta, University of Maryland, USA

Abstract

Optical tweezers have emerged as one of the most promising non-contact manipulation techniques at the small scales; they can successfully trap and transport objects in fluid media. In other words, they can be viewed as miniature robots made out of focused light beams. Autonomous operation requires path planning, which is challenging due to the stochastic Brownian motion of the objects, noise in the imaging based measurements, and the need for fast control update rates.

We develop an approximate partially observable Markov decision process (POMDP) algorithm to compute near-optimal trap locations and velocities that minimize the expected transport time of individual dielectric particles by including collision avoidance and recovery steps. This algorithm is incorporated within a decoupled and prioritized framework to move multiple particles simultaneously, where we use an iterative bipartite graph matching algorithm to optimally assign goal locations to target particles. We demonstrate our approach using 2 micron diameter amorphous silica beads in a holographic tweezer set-up.

Successful runs show that the planner is customizable and can transport specific particles efficiently by either circumventing or trapping other freely diffusing particles. We also show the usefulness of heuristic planning algorithms in arranging biological cells uniformly within nets kept in microfluidic chambers.

I conclude by highlighting the potential impact and challenges of automating multi-cell studies. We believe that path planning will play a significant role in manipulating cells by trapping them indirectly using particles arranged in gripper-like configurations that avoid damage due to direct laser exposure.

Speaker Biography

Ashis Gopal Banerjee is a Postdoctoral Associate in the Computer Science and Artificial Intelligence Laboratory at Massachusetts Institute of Technology. He completed his Ph.D. in Mechanical Engineering at the University of Maryland, College Park, in 2009. Prior to that, he obtained his Master?s Degree in Mechanical Engineering at the University of Maryland in 2006 and Bachelor?s Degree in Manufacturing Science and Engineering at the Indian Institute of Technology, Kharagpur, in 2004. He received the 2009 Best Dissertation Award from the Department of Mechanical Engineering and the 2009 George Harhalakis Outstanding Systems Engineering Graduate Student Award at the University of Maryland. He is a member of the IEEE Robotics and Automation Society Technical Committee on Micro/Nano Robotics and Automation as well as Algorithms for Planning and Control of Robot Motion.

Presentation