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Continuous Graph Partitioning for Camera Network Surveillance *

IFAC Proceedings Volumes 2012年第26期45卷 228-233页

作者： D. Borra F. Pasqualetti F. Bullo Dipartimento di Scienze Matematiche Politecnico di Torino Italy Center for Control Dynamical Systems and Computation University of California Santa Barbara USA

This work focuses on the problem of designing surveillance trajectories for a network of autonomous cameras. As performance criterion we consider the worst-case detection time of static intruders. First, we represent the environment by means of a robotic roadmap. We show that optimal trajectories can be designed via a continuous graph partitioning problem. This minimization problem is convex and not differentiable. Second, we derive an auxiliary convex and differentiable minimization problem whose minimizer provides a solution to the original problem. Third and finally, we develop three distributed algorithms, for the cameras to partition the roadmap, and, consequently, synchronize along a trajectory with minimum worst-case detection time. Different communication protocols are used for the three algorithms.

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Enforced symmetry of the stance phase for the Spring-Loaded Inverted Pendulum

Enforced symmetry of the stance phase for the Spring-Loaded ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Giulia Piovan Katie Byl Center for Control Dynamical Systems and Computation University of California슠Santa Barbara Santa Barbara CA USA

The Spring-Loaded Inverted Pendulum (SLIP) is considered the simplest model to effectively describe bouncing gaits (such as running and hopping) for many legged animals and robots. For this reason, it is has often been used as a model for robot design. A key challenge in using this model, however, is the lack of a closed-form solution for the equations of motion that define the stance phase of its dynamics. This results in the impossibility of analytically predicting its trajectory. Consequently, developing a practical control strategy to operate on the model is computationally intensive, because accurately predicting the step-to-step dynamics is still an unsolved problem. By adding an actuator in series with the spring, we can develop a control law for actuator displacement which enforces a desired trajectory during stance. In particular, for our specific chosen control law, we can compute an analytical solution for the stance phase trajectory. Furthermore, we give examples of higher level control strategies for foothold placement and for keeping the forward velocity or the apex height constant on rough terrain that employ our low-level control laws, and we illustrate through simulations the performance typical of our strategy.

关键词： Trajectory Actuators Springs Mathematical model computational modeling Equations Legged locomotion

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A Gossip Based Heuristic Algorithm for Heterogeneous Multi-Vehicle Routing Problems *

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IFAC Proceedings Volumes 2012年第26期45卷 73-78页

作者： Daniele Rosa Mauro Franceschelli Carla Seatzu Francesco Bullo Dep. of Electrical and Electronic Engineering Univ. of Cagliari Italy Center for Control Dynamical Systems and Computation Univ. of Santa Barbara California USA

In this paper we propose a novel algorithm based on gossip communication for the Heterogeneous Multi-Vehicle Routing (HMVR) problem. A collection of tasks is arbitrarily placed in a plane and a set of robots cooperates to minimize the maximum time required to visit and execute all tasks. Each task (resp. each robot) has different cost (resp. speed). The proposed algorithm relies only upon pairwise asynchronous communications between robots and attempts to balance the routing and execution cost of the task assignment through a heuristic. The proposed heuristic exploits polynomial-time approximation algorithms to solve the Euclidean Traveling Salesman Problem (ETSP). Some characterization of the convergence properties of the algorithm are provided together with extensive simulations to corroborate the results.

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Synchronization Assessment in Power Networks and Coupled Oscillators

Synchronization Assessment in Power Networks and Coupled Osc...

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IEEE Annual Conference on Decision and control

作者： Florian Dorfler Michael Chertkov Francesco Bullo Center for Control Dynamical Systems and Computation University of California at Santa Barbara Theory Division & Center for Nonlinear Studies at LANL and with New Mexico Consortium

ISBN: (纸本)9781467320658

Synchronization problems in complex networks have recently attracted tremendous scientific interested. More-over, assessing the existence, stability, and robustness of synchronous states is a pervasive topic in the operation of power networks. Scientists in both communities have long aimed to identify sharp synchronization conditions as functions of the network topology and parameters. This paper proposes an insightful approach to this problem based on algebraic graph theory. We present a novel synchronization condition applicable to a general coupled oscillator model. We rigorously establish that our condition is exact for various interesting network topologies and parameters. Via statistical studies we show that our condition predicts accurately the existence of stable synchronous solutions for generic networks as well as various power network test cases. From these statistical studies, we conclude that our proposed condition is correct for almost all network topologies and parameters. Indeed, we also show that there exist possibly-thin sets of network topologies and parameters, where our condition is not sufficiently tight.

关键词： Network topology Power grids coupled oscillators Statistical Study Graph theory complex networks

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Generalized solutions to hybrid systems with delays

Generalized solutions to hybrid systems with delays

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IEEE Conference on Decision and control

作者： Jun Liu Andrew R. Teel Department of Automatic Control and Systems Engineering University of Sheffield Sheffield Yorkshire UK Center for Control Dynamical Systems and Computation University of California Santa Barbara CA USA

ISBN: (纸本)9781467320658

We propose a framework that allows to study hybrid systems with delays through generalized concepts of solutions. Such generalized solutions have proved to be suitable for the analysis and design of hybrid control systems. Extending these concepts to systems with delays is motivated by control applications where hybrid feedback control laws play an important role but delays are often inevitable. Our first step characterizes a suitable phase space that is equipped with a suitable notion of convergence. The space of hybrid memory arcs under graphical convergence is considered. Regularity conditions on the hybrid data are then formulated in terms of the graphical topology. The new formulation enables two basic results regarding existence and well-posedness of solutions being established.

关键词： Time domain analysis Convergence Delay Topology Silicon control systems

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Simultaneous Boundary Partitioning and Cameras Synchronization for Optimal Video Surveillance *

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IFAC Proceedings Volumes 2012年第26期45卷 1-6页

作者： F. Zanella F. Pasqualetti R. Carli F. Bullo Department of Information Engineering Università di Padova Via Gradenigo 6/a 35131 Padova Italy Center for Control Dynamical Systems and Computation University of California Santa Barbara USA

This paper proposes a real-time distributed algorithm for a team of smart cameras to self-organize and perform video surveillance of an open boundary. In particular, our algorithm simultaneously partitions the boundary among the cameras, and synchronizes the motion of the cameras to optimize the surveillance performance. We focus on the detection of smart intruders, who are aware of the cameras configuration at each time instant, and who schedule their motion to avoid detection for as long as possible. We consider both the worst-case and the average detection times of smart intruders. Our algorithm achieves minimum worst-case detection time, and, under some reasonable assumptions, constant-factor optimal average detection time.

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A spectral methods-based solution of the Chemical Master Equation for gene regulatory networks

A spectral methods-based solution of the Chemical Master Equ...

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IEEE Conference on Decision and control

作者： Michael Nip João P. Hespanha Mustafa Khammash Center for Control Dynamical Systems and Computation University of California Santa Barbara CA USA Department of Biosystems Science and Engineering ETH-Zürich Basel Switzerland

ISBN: (纸本)9781467320658

We present a new method to approximate the time evolution of the probability density function (PDF) for molecule counts in gene regulatory networks modeled by the Chemical Master Equation (CME). A key feature of our method is that molecular states can be aggregated to reduce the computational burden without the need for assumptions like time-scales separation. The CME is amenable to the use of various spectral methods adapted from partial differential equations and our method results from expanding the solution using carefully selected basis functions. The method is illustrated in the context of an example taken from the field of systems biology.

关键词： Approximation methods Equations Mathematical model Vectors Chemicals Evolution (biology) Biological system modeling

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Adaptive Attention Allocation in Human-Robot systems

Adaptive Attention Allocation in Human-Robot Systems

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American control Conference

作者： Vaibhav Srivastava Amit Surana Francesco Bullo Center for Control Dynamical Systems and Computation University of California Santa Barbara Santa Barbara CA 93106 USA United Technologies Research Center East Hartford CT 06108 USA

ISBN: (纸本)9781457710957

We propose an optimization framework to study two fundamental attention control aspects in human-robot systems: Where and how much attention should the operator allocate? In other words, which information source should be observed by the operator, and how much time duration should be allocated to the information feed in order to optimize the overall performance of the human-robot system? The proposed framework incorporates (i) operator performance constraints, such as error rates and service times based utilization history, (ii) sensor constraints, such as processing/travel time, and (iii) task constraints, such as prioritization. We use a receding horizon approach to solve the resulting dynamic program, leading to efficient policies for operator time duration allocation and sensor selection. We demonstrate our methodology in a distributed surveillance problem.

关键词： Humans Resource management Decision making Optimization Feeds Surveillance Time factors

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Adversarial detection as a zero-sum game

Adversarial detection as a zero-sum game

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IEEE Conference on Decision and control

作者： K. G. Vamvoudakis J. P. Hespanha B. Sinopoli Y. Mo Center for Control Dynamical-systems and Computation (CCDC) University of California Santa Barbara CA USA Electrical and Computer Engineering Department Carnegie Mellon University Pittsburgh PA USA

ISBN: (纸本)9781467320658

We propose a new game theoretic approach to estimate a binary random variable based on a vector of sensor measurements that may be corrupted by an adversary. The problem is formulated as a zero-sum partial information game in which a detector attempts to minimize the probability of error and an attacker attempts to maximize this probability. Explicit mixed policies are computed using the matrix form of the game and exploiting sensor symmetry to reduce complexity and find closed-form solutions.

关键词： Games Estimation Detectors Game theory Vectors Random variables Complexity theory

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Online Learning Algorithm for Stackelberg Games in Problems with Hierarchy

Online Learning Algorithm for Stackelberg Games in Problems ...

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IEEE Annual Conference on Decision and control

作者： K. G. Vamvoudakis F. L. Lewis M. Johnson W. E. Dixon Center for Control Dynamical-systems and Computation (CCDC) University of California Automation and Robotics Research Institute University of Texas at Arlington NASA Ames Research Center Department of Mechanical and Aerospace Engineering University of Florida

ISBN: (纸本)9781467320658

This paper presents an online adaptive optimal control algorithm based on policy iteration reinforcement learning techniques to solve the continuous-time Stackelberg games with infinite horizon for linear systems. This adaptive optimal control method finds in real-time approximations of the optimal value and the Stackelberg-equilibrium solution, while also guaranteeing closed-loop stability. The optimal-adaptive algorithm is implemented as a separate actor/critic parametric network approximator structure for every player, and involves simultaneous continuous-time adaptation of the actor/critic networks. Novel tuning algorithms are given for the actor/critic networks. The convergence to the closed-loop Stackelberg equilibrium is proven and stability of the system is also guaranteed. A simulation example shows the effectiveness of the new online algorithm.

关键词： Stackelberg games Hierarchical control problems adaptive optimal control Social Hierarchy Game theory e-learning infinite horizon Best value algorithms

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