Kumar, Vijay
Email Address
ORCID
Disciplines
Search Results
Now showing 1 - 10 of 11
Publication A Scalable Strategy for Open Loop Magnetic Control of Microrobots Using Critical Points(2016-05-11) Guerrero-Bonilla, Luis; Bhattacharya, Subhrajit; Kumar, VijayA novel scalable strategy for open loop control of ferromagnetic microrobots on a plane using a scalable array of electromagnets is presented. Instead of controlling the microrobot directly, we create equilibrium points in the magnetic force field that are stable and attractive on the plane in which the microrobot is to be controlled. The microrobot moves into these equilibrium points rapidly in presence of low viscous forces, and thus controlling the equilibrium points let us control the microrobot precisely. An unit/cell in the array of electromagnets allows precise control of the microrobot in the unit/cell’s domain. Motion synthesis across multiple overlapping domains allows control of the microrobot in large regions across the array. We perform numerical analysis and demonstrate the control of the ferromagnetic microrobot using the proposed method through simulations.Publication Single Cell Manipulation using Ferromagnetic Composite Microtransporters(2010-01-29) Sakar, Mahmut Selman; Steager, Edward B; Pappas, George J; Kumar, Vijay; Kim, Dal Hyung; Kim, Min JunFor biomedical applications, such as single cell manipulation, it is important to fabricate microstructures that can be powered and controlled wirelessly in fluidic environments. In this letter, we describe the construction and operation of truly micron-sized, biocompatible ferromagnetic microtransporters driven by external magnetic fields. Microtransporters were fabricated using a simple, single step fabrication method and can be produced in large numbers. We demonstrate that they can be navigated to manipulate single cells with micron-size precision without disturbing the local environment.Publication Elastic Multi-Particle Systems for Bounded-Curvature Path Planning(2008-06-11) Ahmadzadeh, Ali; Jadbabaie, Ali; Pappas, George J; Kumar, VijayThis paper investigates a path planning algorithm for Dubins vehicles. Our approach is based on approximation of the trajectories of vehicles using sequence of waypoints and treating each way point as a moving particle in the space. We define interaction forces between the particles such that the resulting multi-particle system will be stable, moreover, the trajectories generated by the waypoints in the equilibria of the multi-particle system will satisfy all of the hard constraint such as bounded-curvature constraint and obstacle avoidance.Publication Maintaining Connectivity in Mobile Robot Networks(2009-03-28) Michael, Nathan; Zavlanos, Michael M; Kumar, Vijay; Pappas, George JWhile there has been significant progress in recent years in the study of estimation and control of dynamic network graphs, limited attention has been paid to the experimental validation and verification of such algorithms on distributed teams of robots. In this work we conduct an experimental study of a non-trivial distributed connectivity control algorithm on a team of seven nonholonomic robots as well as in simulation. The implementation of the algorithm is completely decentralized and asynchronous, assuming that each robot only has access to its pose and knowledge of the total number of robots. All other necessary information is determined via message passing with neighboring robots. We show that such algorithms, requiring complex inter-agent communication and coordination, are feasible as well as highly successful in enabling a network of robots to adapt to disturbances while preserving connectivity.Publication Controlling Swarms of Robots Using Interpolated Implicit Functions(2005-04-01) Chaimowicz, Luiz; Michael, Nathan D; Kumar, VijayWe address the synthesis of controllers for large groups of robots and sensors, tackling the specific problem of controlling a swarm of robots to generate patterns specified by implicit functions of the form s(x, y) = 0. We derive decentralized controllers that allow the robots to converge to a given curve S and spread along this curve. We consider implicit functions that are weighted sums of radial basis functions created by interpolating from a set of constraint points, which give us a high degree of control over the desired 2D curves. We describe the generation of simple plans for swarms of robots using these functions and illustrate.Publication Information Driven Coordinated Air-Ground Proactive Sensing(2005-04-01) Grocholsky, Ben; Swaminathan, Rahul; Keller, James; Kumar, Vijay; Pappas, George JThis paper concerns the problem of actively searching for and localizing ground features by a coordinated team of air and ground robotic sensor platforms. The approach taken builds on well known Decentralized Data Fusion (DDF) methodology. In particular, it brings together established representations developed for identification and linearized estimation problems to jointly address feature detection and localization. This provides transparent and scalable integration of sensor information from air and ground platforms. As in previous studies, an Information theoretic utility measure and local control strategy drive the robots to uncertainty reducing team configurations. Complementary characteristics in terms of coverage and accuracy are revealed through analysis of the observation uncertainty for air and ground on-board cameras. Implementation results for a detection and localization example indicate the ability of this approach to scalably and effciently realize such collaborative potential.Publication Inertial Velocity and Attitude Estimation for Quadrotors: Supplementary Material(2018-10-01) Svacha, James B; Mohta, Kartik; Watterson, Michael; Loianno, Giuseppe; Kumar, VijayPublication Motion Primitive-Based Graph Planning for Mobile Manipulation With Closed-Chain Systems(2012-01-01) Gray, Steven R; Clingerman, Christopher; Kumar, Vijay; Likhachev, MaximMotion primitive-based (lattice-based) graphs have been used extensively in navigation, but application to high-dimensional state-spaces has remained limited by computational complexity. In this work, we show how these graphs can be applied to mobile manipulation. The formation of closed chains in tasks that involve contacts with the environment may reduce the number of available degrees of freedom but add complexity in terms of constraints in the high-dimensional state space. We propose a novel method to reduce dimensionality by abstracting away the constraints associated with closed-chain systems. Proofs are introduced for the application to graph-search and its theoretical guarantees of optimality. The dimensionality-reduction is done in a manner that enables finding optimal solutions to low-dimensional problems which map to correspondingly optimal full-dimensional solutions. We demonstrate the usefulness of our method with simulation results; we apply our approach to moving an object in 2D using a mobile manipulation platform with a planar arm.Publication Planning and Control of Mobile Robots in Image Space from Overhead Cameras(2005-04-01) Rao, Rahul S; Kumar, Vijay; Taylor, Camillo JIn this work, we present a framework for the development of a planar mobile robot controller based on image plane feedback. We show that the design of such a motion controller can be accomplished in the image plane by making use of a subset of the parameters that relate the image plane to the ground plane, while still leveraging the simplifications offered by modeling the system as a differentially flat system. Our method relies on a waypoint-based trajectory generator, with all the waypoints specified in the image, as seen by an overhead observer. We present some results from simulation as well as from experiments that validate the ideas presented in this work and discuss some ideas for future workPublication Stochastic Modeling and Control of Biological Systems: The Lactose Regulation System of Escherichia Coli(2009-01-01) Julius, Agung; Halász, Ádám; Sakar, M Selman; Rubin, Harvey; Kumar, Vijay; Pappas, George JIn this paper, we present a comprehensive framework for stochastic modeling, model abstraction, and controller design for a biological system. The first half of the paper concerns modeling and model abstraction of the system. Most models in systems biology are deterministic models with ordinary differential equations in the concentration variables. We present a stochastic hybrid model of the lactose regulation system of E. coli bacteria that capture important phenomena which cannot be described by continuous deterministic models.We then show that the resulting stochastic hybrid model can be abstracted into a much simpler model, a two-state continuous-time Markov chain. The second half of the paper discusses controller design for a specific architecture. The architecture consists of measurement of a global quantity in a colony of bacteria as an output feedback and manipulation of global environmental variables as control actuation. We show that controller design can be performed on the abstracted (Markov chain) model and implementation on the real model yields the desired result.