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Institute for Robotics and Intelligent Machines (IRIM)

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Author: Zhang, Fumin × search.filters.applied.f.isOrgUnitOfPublicationTitle: Institute for Robotics and Intelligent Machines (IRIM) × search.filters.applied.f.resourcesubtype: Pre-print ×

Publication Search Results

Now showing 1 - 5 of 5
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    Trend and Bounds for Error Growth in Controlled Lagrangian Particle Tracking
    (Georgia Institute of Technology, 2012-12-18) Szwaykowska, Klementyna ; Zhang, Fumin
    This paper establishes the method of controlled Lagrangian particle tracking (CLPT) to analyse the offsets between physical positions of marine robots in the ocean and simulated positions of controlled particles in an ocean model. The offset, which we term the CLPT error, demonstrates distinguished characteristics not previously seen in drifters and floats that cannot be actively controlled. The CLPT error growth over time is exponential until it reaches a turning point that only depends on the resolution of the ocean model. After this turning point, the error growth slows down significantly to polynomial functions of time. In the ideal case, a theoretical upper threshold on exponential growth of CLPT error can be derived. These characteristics are proved theoretically, verified via simulation, and justified with ocean experimental data. The method of CLPT may be applied to improve the accuracy of ocean circulation models and the performance of navigation algorithms for marine robots.
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    Experimental Validation of Source Seeking with a Switching Strategy
    (Georgia Institute of Technology, 2011) Wu, Wencen ; Zhang, Fumin
    We design a switching strategy for a group of robots to search for a local minimum of an unknown noisy scalar field. Starting with individual exploration, the robots switch to cooperative exploration only when they are not able to locate the field minimum based on the information collected individually. In order to test and demonstrate the switching strategy in real-world environment, we implement the switching strategy on a multi-robot test-bed. The behaviors of a group of robots are compared when different parameters for exploration are adopted. Especially, we observe the effect of memory lengths on the switching behaviors as predicted by theoretical results. The experimental results also justify the effects of different formation sizes and noise attenuation levels on the performance of the cooperative H∞ filter that are utilized in the cooperative exploration phase.
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    Steady three dimensional gliding motion of an underwater glider
    (Georgia Institute of Technology, 2011) Zhang, Shaowei ; Yu, Jiancheng ; Zhang, Aiqun ; Zhang, Fumin
    Underwater Gliders have found broad applications in ocean sampling. In this paper, the nonlinear dynamic model of the glider developed by the Shenyang Institute of Automation, Chinese Academy of Sciences, is established. Based on this model, we solve for the parameters that characterize steady state spiraling motions of the glider. A set of nonlinear equations are simplified so that a recursive algorithm can be used to find the solutions.
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    Curve Tracking Control for Autonomous Vehicles with Rigidly Mounted Range Sensors
    (Georgia Institute of Technology, 2009) Kim, Jonghoek ; Zhang, Fumin ; Egerstedt, Magnus B.
    In this paper, we present feedback control laws for an autonomous vehicle with rigidly mounted range sensors to track a desired curve. In particular, we consider a vehicle that has a group of rays around two center rays that are perpendicular to the velocity of the vehicle. Under such a sensor configuration, singularities are bound to occur in the curve tracking feedback control law when tracking concave curves. To overcome this singularity, we derive a hybrid strategy of switching between control laws when the vehicle gets close to singularities. Rigorous proof and extensive simulation results verify the validity of the proposed feedback control law.
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    Control of coordinated patterns for ocean sampling
    (Georgia Institute of Technology, 2007) Zhang, Fumin ; Fratantoni, David M. ; Paley, Derek A. ; Lund, John M. ; Leonard, Naomi Ehrich
    A class of underwater vehicles are modelled as Newtonian particles for navigation and control. We show a general method that controls cooperative Newtonian particles to generate patterns on closed smooth curves. These patterns are chosen for good sampling performance using mobile sensor networks. We measure the spacing between neighbouring particles by the relative curve phase along the curve. The distance between a particle and the desired curve is measured using an orbit function. The orbit value and the relative curve phase are then used as feedback to control motion of each particle. From an arbitrary initial configuration, the particles converge asymptotically to form an invariant pattern on the desired curves. We describe application of this method to control underwater gliders in a field experiment in Buzzards Bay, MA in March 2006.