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Proceedings ArticleDOI

An application of sequential composition control to cooperative systems

TLDR
This paper extends the standard sequential composition by introducing a novel approach to compose multiple sequential composition controllers towards cooperative control of an inverted pendulum system collaborating with a second-order DC motor for cooperative swing-up maneuvers.
Abstract
Sequential composition is an effective supervisory control approach for addressing challenging control problems on complex dynamical systems. It constructs a back-chaining sequence of controllers to achieve the control objective using simple local controllers. Although sequential composition works properly for a single system, it is not designed for cooperative systems. This paper extends the standard sequential composition by introducing a novel approach to compose multiple sequential composition controllers towards cooperative control. Given two or more systems, cooperation is achieved by composing each of the systems' supervisory finite-state machines, together with the estimation of the domains of attraction of the composed controllers. We present the simulation and experimental results of an inverted pendulum system collaborating with a second-order DC motor for cooperative swing-up maneuvers.

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Citations
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Journal ArticleDOI

A fast sampling method for estimating the domain of attraction

TL;DR: In this paper, a sampling approach is proposed to estimate the domain of attraction (DoA) of nonlinear systems in real time, which is validated to approximate the DoAs of stable equilibria.
Journal ArticleDOI

Robot Contact Language for Manipulation Planning

TL;DR: A contact-based language for robotic manipulation and planning, based on the contact between a collection of objects, robots, and surfaces, is proposed, which considers making and breaking contact as the bridge between high-level planning and low-level controllers.
Journal ArticleDOI

Learning Sequential Composition Control

TL;DR: A learning approach to augment the standard sequential composition framework by using online learning to handle unforeseen situations and the results show that in both cases a new controller can be rapidly learned and added to the supervisory control structure.
Proceedings ArticleDOI

Towards cooperative sequential composition control

TL;DR: The standard sequential composition is extended by introducing a novel approach to compose multiple sequential composition controllers towards cooperative control, which can fulfill the tasks which are not possible to satisfy with the original controllers individually.
Proceedings ArticleDOI

ROS-based SLAM and Navigation for a Gazebo-Simulated Autonomous Quadrotor

TL;DR: In this paper, a robotic operating system based on autonomous simultaneous localization and mapping (SLAM), and robot navigation implementation of a Parrot AR.2.0 quadrotor, which is equipped with a laser scanner and inertial measurement unit, is presented.
References
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Book

Introduction to Graph Theory

TL;DR: In this article, the authors introduce the concept of graph coloring and propose a graph coloring algorithm based on the Eulers formula for k-chromatic graphs, which can be seen as a special case of the graph coloring problem.
MonographDOI

Planning Algorithms: Introductory Material

TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
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Introduction to Discrete Event Systems

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Sampling-based algorithms for optimal motion planning

TL;DR: In this paper, the authors studied the asymptotic behavior of the cost of the solution returned by stochastic sampling-based path planning algorithms as the number of samples increases.
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