Person:

Zhang, Fumin

Permanent Link

https://hdl.handle.net/1853/71883

Associated Organization(s)

Organizational Unit

School of Electrical and Computer Engineering

Full item page

Publication Search Results

Now showing 1 - 10 of 32

Maritime Robotic Sensing Networks

(Georgia Institute of Technology, 2021-08-25) Zhang, Fumin

The Ocean is playing an ever more important role for the future of mankind. Larger variety of marine robots have been developed and commercialized during the last two decades. These robots may serve as networked mobile sensing platforms that are able to collect data in the maritime environment in unprecedented ways, which post higher goals for autonomy never achieved before. This talk gives an overview of autonomous underwater vehicles and their applications for data collection in a complex ocean environment.
Mobile Data Collection in an Aquatic Environment: Cyber Maritime Cycles for Distributed Autonomy

(Georgia Institute of Technology, 2019-03-06) Zhang, Fumin

There is a perceivable trend for robots to serve as networked mobile sensing platforms that are able to collect data in aquatic environments in unprecedented ways. We argue that the effective transformation between Eulerian and Lagrangian data streams represents a fundamental principle underlying many ongoing research efforts. Timely transformation of data streams is the major challenge to construct cyber cycles that are needed by marine autonomy. Data-driven machine learning methods have great potential but are constrained by special difficulties for underwater communication. A distributed autonomy structure that is able to cope with the limited information sharing is envisioned as the future. This challenge can only be addressed by interdisciplinary efforts from researchers in underwater acoustics, underwater networking, and marine robotics. This talk will discuss recent advancements towards integrating marine robotic platforms with underwater communication and networking technology. In particular, we will address the influences from both environmental motions (caused by ocean flow) and controllable platform motion on the transformation of the data streams. Even though such motions have been known to degrade the performance of acoustic communication and networking, the quantitative relationships have yet to be established, calling for tremendous efforts for theoretical analysis, simulations, and experimental study. One of our approaches, named motion tomography (MT), develop generic environmental models (GEMs) to combine computational ocean models with real-time data streams collected by mobile sensing platforms to provide high-resolution predictions of ocean current in a small spatial area around the mobile platforms. With better known environmental motion, the performance of acoustic networking can be better analyzed as demonstrated through lab-based experiments leveraging micro autonomous vehicles equipped with acoustic modems. Our efforts also indicate that future research requires an open and cost-effective experimental infrastructure that integrates marine robotic platforms, an underwater acoustic device, and underwater networking equipment.
Dissipativity-Based Teleoperation with Time-Varying Communication Delays

(Georgia Institute of Technology, 2013-09) Varnell, Paul ; Zhang, Fumin

We analyze the effects of communication delays in teleoperation systems using dissipativity theory along with explicit models of the operator and robot. We utilize a simple model of the operator's behavior that describes human pointing motions, as generated by an interface such as a mouse pointer or tablet, and we use a robot model that is suitable for mobile robots or robotic manipulators. Using dissipativity conditions for stability, we show that the communication delays can be compensated for in the robot controller with a relatively simple extension to a controller designed for the situation without delays. We also show that the communication delays can lead to problems for human pointing in certain situations; specifically, if the operator overshoots their target, it may lead to instability unless corrective action is taken by the user interface. Simulation is shown to validate the result
Robust Geometric Formation Control of Multiple Autonomous

(Georgia Institute of Technology, 2013-06) Yang, Huizhen ; Wang, Chuanfeng ; Zhang, Fumin

This paper develops a robust controller for autonomous underwater vehicles with bounded time delays, so that the AUVs form and keep a desired formation shape and track a desired trajectory. We use a six-degree-of-freedom dynamic model for each AUV to describe its motions in the three-dimensional space. We design an orientation controller based on feedback linearization, so that the orientation of each AUV converges to its desired value. We derive formation dynamics of AUVs and decouple the dynamics into a formation shape and a formation center, using the Jacobi transform. We treat couplings in the formation dynamics as perturbations and design a robust formation-keeping controller to tolerate both the perturbations and the time delays. We demonstrate the effectiveness of our controller in simulations.
Robustness of a Class of Three-Dimensional Curve Tracking Control Laws Under Time Delays and Polygonal State Constraints

(Georgia Institute of Technology, 2013-06) Malisoff, Michael ; Zhang, Fumin

We analyze the robustness of a class of controllers that enable three-dimensional curve tracking of free moving particles. By building a strict Lyapunov function and robustly forwardly invariant sets, we show input-to-state stability under predictable tolerance and safety bounds that guarantee robust- ness under control uncertainty, input delays, and a class of polygonal state constraints. Such understanding may provide certified performance when the control laws are applied to real life systems. We demonstrate our findings in simulations
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.
Controlled Lagrangian Particle Tracking Error Under Biased Flow Prediction

(Georgia Institute of Technology, 2013) Szwaykowska, Klementyna ; Zhang, Fumin

In this paper we model the controlled Lagrangian particle tracking (CLPT) error for marine vehicles moving in an ocean flow field, with guidance from ocean models. We linearize the error about the nominal modeled trajectory of the system and derive an exact expression for the linearized error in the case of constant modeled ocean flow. We show that this simple error model can be used to estimate error in predicted positions of autonomous vehicles, using data from a field deployment of autonomous underwater gliders in Long Bay, SC, in winter 2012.
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.
An Analytical Model of the CAN Bus for Online Schedulability Test

(Georgia Institute of Technology, 2012-12-04) Shi, Zhenwu ; Zhang, Fumin

Controller area network (CAN) is a prioritybased bus that supports real-time communication. Existing schedulability analysis for the CAN bus is peformed at the design stage, by assuming that all message information is known in advance. However, in pratice, the CAN bus may run in a dynamic environment, where complete specifications may not be available at the design stage and operational requirements may change at system run-time. In this paper, we develop an analytical model that describes the dynamics of message transmission on the CAN bus. Based on this analytical timing model, we then propose an online test that effectively checks the schedulability of the CAN bus, in the presence of online adjustments of message streams. Simulations show that the online test can accurately report the loss of scheduability on the CAN bus.
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.