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Zhang, Fumin

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Start date: 2010 × End date: 2019 × Author: Wu, Wencen ×

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Now showing 1 - 5 of 5
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    A Bio-inspired Plume Tracking Algorithm for Mobile Sensing Swarms in Turbulent Flow
    (Georgia Institute of Technology, 2013-05) Chang, Dongsik ; Wu, Wencen ; Webster, Donald R. ; Weissburg, Marc J. ; Zhang, Fumin
    We develop a plume tracking algorithm for a swarm of mobile sensing agents in turbulent flow. Inspired by blue crabs, we propose a stochastic model for plume spikes based on the Poisson counting process, which captures the turbulent characteristic of plumes. We then propose an approach to estimate the parameters of the spike model, and transform the turbulent plume field detected by sensing agents into a smoother scalar field that shares the same source with the plume field. This transformation allows us to design path planning algorithms for mobile sensing agents in the smoother field instead of in the turbulent plume field. Inspired by the source seeking behaviors of fish schools, we design a velocity controller for each mobile agent by decomposing the velocities into two perpendicular parts: the forward velocity incorporates feedback from the estimated spike parameters, and the side velocity keeps the swarm together. The combined velocity is then used to plan the path for each agent in the swarm. Theoretical justifications are provided for convergence of the agent group to the plume source. The algorithms are also demonstrated through simulations.
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    Bio-inspired Source Seeking with no Explicit Gradient Estimation
    (Georgia Institute of Technology, 2012-09) Wu, Wencen ; Couzin, Iain D. ; Zhang, Fumin
    Inspired by behaviors of fish groups seeking darker (shaded) regions in environments with complex lighting variations, we develop distributed source-seeking algorithms for a group of sensing agents with no explicit gradient estimation. We choose a baseline for agent groups and decompose the velocity of each agent into two parts. The first part, which is perpendicular to the baseline, is chosen to be proportional to the measurements, agreeing with observations from fish groups. The second part, which is parallel to the baseline, can be designed to control the relative distances among the agents. This decomposition is leveraged to implement formation- maintaining strategies and source seeking behaviors for the entire group. We prove that the moving direction of a group will converge towards the gradient direction while the formation is maintained.
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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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    A Switching Strategy for Robust Cooperative Exploration
    (Georgia Institute of Technology, 2010-12) Wu, Wencen ; Zhang, Fumin
    This paper develops a switching strategy for networked mobile sensing agents to automatically decide when to perform individual exploration and when to perform cooperative exploration of an unknown scalar field corrupted by time-varying non-Gaussian noises. The switching condition from individual exploration to cooperative exploration is based on Razumikhin theorem, and the change of the signal-to-noise ratio (SNR) serves as the switching condition from cooperative exploration to individual exploration. A cooperative H∞ filter is proposed when the agents are collaborating. Sufficient conditions are derived for the cooperative H∞ filter to converge. This switching strategy balances the mobility of the agents and the exploring accuracy. Simulation results demonstrate that with the switching strategy, a group of sensing agents can succeed in finding a local minimum of an unknown scalar field efficiently.
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    Curvature Based Cooperative Exploration of Three Dimensional Scalar Fields
    (Georgia Institute of Technology, 2010) Wu, Wencen ; Zhang, Fumin
    We develop strategies for controlled motion and filtering performed by a mobile sensor network to cooperatively explore an unknown 3D scalar field. In order to estimate the principal directions and principal curvatures of a desired level surface of the field which are used as feedback by the motion control law, we apply a non-analytic curvature estimation algorithm and prove the sufficient and necessary conditions under which this algorithm can provide reliable estimates. A differential geometric approach is followed in developing provably convergent steering control laws to control the center of the sensor platform formation to track one of the lines of curvature on a detected level surface of the scalar field.