Research Assistant, Computer Science resume example

• Leading a team of undergraduate students for several projects in robotics in Multi- Robot System Lab, Rice University.
• Designed a novel algorithm for motion planning autonomous vehicles.
• Designed a new algorithm for the recovery of large number of agents.
• Collaborated in a uniform massive control project to position control of a very large scale system by using uniform control/
• Mentored control systems and robotic projects in ARAS team, Iran.

Publications:

• G.Claire, J. McLurkin, “K redundant Trees for Safe and efficient Multirobot Recovery in Complex Environments”, Autonomous Robots [Ready to submit].
• G.Claire, E.Masehian, “Robot Path Planning in 3D Space Using Binary Integer Programming“, InternationalJournal of Mechanical Systems Science and Engineering,bVolume 29, pp. 26-31, May 2007.
• G. Claire, and J.McLurkin, "Distributed Configuration Space Path Planning for Multi-Robot Manipulation ", ICRA 2014 [to be submitted].
• G. Claire, L. Schmidt, M.Jellins and J.McLurkin, "K-redundant Trees for Safe and Efficient Multi-robot Recovery in Complex Environments", International Symposium to Research Robot (ISRR) 2013 [submitted].
• A. Becker, E.D. Demaine,S.P. Feketez, G.Claire, James McLurkin, "Reconfiguring Massive Particle Swarms with Limited, Global Control", ALGOSENSORS 2013, France, Sept 2013
• A.Becker, G.Claire, J.Werfel, M.Rubenstein, J.McLurkin,”Massive Uniform Manipulation:Controlling Large Populations of Simple Robots with a Common Input Signal”, IROS 2013.
• M.Rubenstein, A.Cabrera, J.Werfel, G.Claire, J.McLurkin, R. Nagpal, "Collective Transport of Complex Objects by Simple Robots: Theory and Experiments, AAMAS 2013, MN, USA.
• G.Claire, J. McLurkin, “MaximumLeaf Spanning Trees for Efficient MultiRobot Recovery with Connectivity Guarantees”, International Symposium of Distributed Autonomous Robotic Systems (DARS), Nov 2012.
• G. Claire, E.Masehian, M.T.H. Beheshti, ”Binary Integer Programming Model of Path planning for Point Robots”, IEEE Industrial Electronic society Conference(IECON), Taiwan, Nov 2007.
• E.Masehian, G.Claire,” Motion Planning and Control of Mobile Robot using Linear Matrix Inequalities”, In proceedings of IEEE Conference on Intelligent Robotics and Automation(IROS), CA, USA, Nov-Oct 2007
• G.Claire, M.T.H. Beheshti, ”Applied H infinity controller design for Flexible Transmission System”, In proceedings of IEEE Industrial Electronic society Conference, Taiwan, Nov. 2007.
• G.Claire, E.Masehian, “Novel Fuzzy Control of Bi-wheeled Mobile Robot on Reference Path”, Spain, ICABB 2010.

Research Projects

K-redundant Trees for Safe and Efficient Multi-robot Recovery:

This projects presents a self-stabilizing distributed algorithm to recover a large number of robots safely and efficiently in a goal location. Previously, we designed a distributed algorithm, called DMLST, to recover robots Our approach constructed a maximum-leaf spanning tree for physical routing, such that interior robots remained stationary and leaf robots move. In this paper, we extend our approach to k-DMLST recovery that provides k-connectivity in the network, meaning that each robot is connected to the goal location through k trees. This redundancy provides stronger network connectivity by reducing the probability of losing the parent during recovery. We also propose an efficient navigation algorithm for the motion of robots which guarantees forward progress during the recovery. k-DMLST recovery has been tested and compared with other methods in simulation, and implemented on a physical multi-robot system. A basic recovery algorithm fails in all experiments, and DMLST recovery is not successful in few trials However, k-DMLST recovery efficiently succeeds in all trials.

Massive Uniform Manipulation:

In this project we investigate control of mobile robots that move in a 2D workspace using three different system models. We focus on a model that uses broadcast control inputs specified in the global reference frame.In an obstacle-free workspace this system model is uncontrollable because it has only two controllable degrees of freedom—all robots receive the same inputs and move uniformly. We prove that adding a single obstacle can make the system controllable, for any number of robots. We provide a position control algorithm, and demonstrate through extensive testing with human subjects that many manipulation tasks can be reliably completed, even by novice users, under this system model, with performance benefits compared to the alternate models. We compare the sensing, computation, communication, time, and bandwidth costs for all three system models. Results are validated with extensive simulations and hardware experiments using over 100 robots.

Collective Transport of Complex Objects by Simple Robots :

In this project we investigate a simple decentralized strategy for collective transport in which each agent acts independently without explicit coordination. Using a physics-based model, we prove that this strategy is guaranteed to successfully transport a complex object to a target location, even though each agent only knows the target direction and does not know the object shape, weight, its own position, or the position and number of other agents. Using two robot hardware platforms, and a wide variety of complex objects, we validate the strategy through extensive experiments. Finally, we present a set of experiments to demonstrate the versatility of the simple strategy, including transport by 100 robots, transport of an actively moving object, adaptation to change in goal location, and dealing with partially observable goals.