From Algorithms to Architectures in Cyber-Physical Networks

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Cyber-Physical Systems on 17/04/2014, available online:http://dx.doi.org/10.1080/23335777.2015.105623

Cloud-Based Optimization: A Quasi-Decentralized Approach to Multi-Agent Coordination

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Presented at the 2014 IEEE 53rd Annual Conference on Decision and Control (CDC), December 15-17, 2014, Los Angeles, CA.DOI: 10.1109/CDC.2014.7040430New architectures and algorithms are needed to reflect the mixture of local and global information that is available as multi-agent systems connect over the cloud. We present a novel architecture for multi-agent coordination where the cloud is assumed to be able to gather information from all agents, perform centralized computations, and disseminate the results in an intermittent manner. The cloud model accounts for delays in communications both when sending data to and receiving data from the agents. This architecture is used to solve a multi-agent optimization problem in which each agent has a local objective function unknown to the other agents and in which the agents are collectively subject to global constraints. Leveraging the cloud, a dual problem is formulated and solved by finding a saddle point of the associated Lagrangian

Approximate Manipulability of Leader-Follower Networks

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 50th IEEE Conference on Decision and Control and European Control Conference, December 12-15, 2011, Orlando, FL, USA.We introduce the notion of manipulability to leader-follower networks as a tool to analyze how effective inputs injected at a leader node are in terms of their impact on the movements of the follower nodes, as a function of the interaction topologies and agent configurations. Classic manipulability is an index used in robotics for analyzing the singularity and efficiency of configurations of robot-arm manipulators. To define similar notions for leader-follower networks, we use a rigid-link approximation of the follower dynamics and under this assumption, we prove that the instantaneous follower velocities can be uniquely determined by that of the leader's, which allows us to define a meaningful manipulability index of the leader-follower network

Optimal Control of Switched Dynamical Systems Under Dwell Time Constraints

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Presented at the 2014 IEEE 53rd Annual Conference on Decision and Control (CDC), December 15-17, 2014, Los Angeles, CA.DOI: 10.1109/CDC.2014.7040117This paper addresses the problem of optimally scheduling the mode sequence and mode duration for switched dynamical systems under dwell time constraints that describe how long a system has to stay in a mode before they can switch to another mode. The schedule should minimize a given cost functional defined on the state trajectory. The topology of the optimization space for switched dynamical systems with and without dwell time constraints is investigated and it is shown that the notion of local optimality must be replaced by stationarity with regards to a suitably chosen optimality function when dwell time constraints are present. Hence, an optimality function is proposed to characterize the solution to the dwell time problem as points that satisfy optimality condition defined in terms of optimality function. A conceptual algorithm is presented to solve the mode scheduling problem and its convergence to stationary points is proved. A numerical example is given to highlight the algorithm

Multi-robot routing for servicing spatio-temporal requests: A musically inspired problem

Presented at the 4th IFAC Conference on Analysis and Design of Hybrid Systems, June 6-8, 2012, Eindhoven, Netherlands.DOI: 10.3182/20120606-3-NL-3011.00051In this paper, we consider the problem of routing multiple robots to service spatially distributed requests at specified time instants. As a motivating example, we present the Robot MusicWall, a musically instrumented surface where planar positions correspond to distinct notes of an instrument. Multiple robots with the ability to traverse the wall can effectively “play” a piece of music by reaching positions on the wall that correspond to the musical notes in the piece, at specified time instants.We show that the multi-robot routing problem for servicing such spatio-temporal requests can be formulated as a pure assignment problem with the resulting reduction in complexity. Moreover, we derive the minimum number of robots required to service such requests

Spatio-Temporal Multi-Robot Routing

Copyright © 2015 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.automatica.2015.07.01In this paper, we consider the problem of routing multiple robots to service spatially distributed requests at specified time instants. We show that such a routing problem can be formulated as a pure assignment problem. Additionally, we incorporate connectivity constraints into the problem by requiring that range-constrained robots ensure a connected information exchange network at all times. We discuss the feasibility aspects of such a spatio-temporal routing problem, and derive the minimum number of robots required to service the requests. Moreover, we explicitly construct the corresponding routes for the robots, with the total length traveled as the cost to be minimized

Motion Preference Learning

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the American Control Conference, San Francisco, CA, June 2011.In order to control systems to meet subjective criteria, one would like to construct objective functions that accurately represent human preferences. To do this, we develop robust estimators based on convex optimization that, given empirical, pairwise comparisons between motions, produce both (1) objective functions that are compatible with the expressed preferences, and (2) global optimizers (i.e., “best motions”) for these functions. The approach is demonstrated with an example in which human and synthetic motions are compared

Endogenous Inequality

Does the market economy exacerbate inequality across households? In a capitalistick society, does the rich maintain a high level of wealth at the expense of the poor? Or would an accumulation of the wealth by the rich eventually trickle down to the poor and pull the latter out of poverty? This paper presents a theoretical framework, in which one can address these questions in a systematic way. The model focuses on the role of credit market, which determines the joint evolution of the distribution of wealth and the interest rate. A complete characterization of the steady states is provided. Under some configurations of the parameter values, the model predicts an endogenous and permanent separation of the population into the rich and the poor, where the rich maintains a high level of wealth partially due to the presence of the poor. Under others, the model predicts the Kuznets curve, i.e., the wealth eventually trickles down from the rich to the poor, eliminating inequality in the long run.Imperfect Credit Markets, Distribution of Wealth, Endogenous Inequality, Trickle-Down, The Kuznets Curve

Securing Multiagent Systems Against a Sequence of Intruder Attacks

Presented at the 2012 American Control Conference, June 27-29, Montréal, Canada.In this paper, we discuss the issue of security in multiagent systems in the context of their underlying graph structure that models the interconnections among agents. In particular, we investigate the minimum number of guards required to counter an infinite sequence of intruder attacks with a given sensing and response range of an individual guard. We relate this problem of eternal security in graphs to the domination theory in graphs, providing tight bounds on the number of guards required along with schemes for securing a multiagent system over a graph

Motion Description Language-Based Topological Maps for Robot Navigation

(c) 2008 International PressFirst published in Communications in Information and Systems, Vol. 8, No. 2, pp. 171-184, 2008, published by International Press.Robot navigation over large areas inevitably has to rely on maps of the environment. The standard manner in which such maps are defined is through geometry, e.g. through traversability grid maps or through a division of the environment into free-space and obstacle-space. In this paper, we combine certain aspects of the geometric maps, through the notion of distinctive places, with a topological description of how these places are related. What is novel is the idea that the adjacency relation is defined by the existence of a control law that drives the robot between topologically connected places. Moreover, these maps can be automatically constructed based on the premise that the nodes correspond to places associated with a heightened control activity