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Research Papers

A Geometric Approach to Dynamically Feasible, Real-Time Formation Control

[+] Author and Article Information
D. H. A. Maithripala

 Siemens Industry Inc., 501 Fountain Parkway, Grand Prairie, TX 75050diyogu.maithripala@siemens.com

D. H. S. Maithripala

Department of Mechanical Engineering, Faculty of Engineering, University of Peradeniya, Peradeniya 20400, Sri Lankasmaithri@pdn.ac.lk

S. Jayasuriya

Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843-3123sjayasuriya@tamu.edu

J. Dyn. Sys., Meas., Control 133(2), 021010 (Mar 09, 2011) (14 pages) doi:10.1115/1.4003209 History: Received October 18, 2009; Revised August 31, 2010; Published March 09, 2011; Online March 09, 2011

We propose a framework for synthesizing real-time trajectories for a wide class of coordinating multi-agent systems. The class of problems considered is characterized by the ability to decompose a given formation objective into an equivalent set of lower dimensional problems. These include the so called radar deception problem and the formation control problems that fall under formation keeping and/or formation reconfiguration tasks. The decomposition makes the approach scalable, computationally economical, and decentralized. Most importantly, the designed trajectories are dynamically feasible, meaning that they maintain the formation while satisfying the nonholonomic and saturation type velocity and acceleration constraints of each individual agent. The main contributions of this paper are (i) explicit consideration of second order dynamics for agents, (ii) explicit consideration of nonholonomic and saturation type velocity and acceleration constraints, (iii) unification of a wide class of formation control problems, and (iv) development of a real-time, distributed, scalable, computationally economical motion planning algorithm.

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Copyright © 2011 by American Society of Mechanical Engineers
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Figures

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Figure 2

Configuration of the ith subsystem for the formation reconfiguration problem

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Figure 3

Configuration of the ith subsystem for the radar deception problem

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Figure 4

Formation keeping motion for six mobile agents

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Figure 5

Speed and steer controls for each of the six agents for the coordinated motion shown in Fig. 4

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Figure 6

Formation reconfiguration motion for six agents

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Figure 7

Speed and steer controls for each of the six agents for the coordinated motion shown in Fig. 6

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Figure 8

Four UAVs deceiving a radar network of four radars through the generation of a phantom track

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Figure 9

Speed and steer, along with their upper and lower bounds, for each of the four UAVs and the UAV representing the phantom

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Figure 10

Simple model of a mobile robot, where (x,y) are positions and v1(t),v2(t) are controls in the x,y directions

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Figure 11

Robotic model, where (x,y) are positions, θ is orientation, v1(t) is speed, and v2(t) is steer control of robot

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Figure 12

Simplified UAV kinematic model, where (x,y,z) are positions, θ is heading angle, β is flight path angle, α is bank angle, v1(t) is speed, v2(t) is pitch, v3(t) is yaw, and v4(t) is roll of UAV

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Figure 1

Motion planning algorithm based on a switching control strategy

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