This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

System Identification I

Smoothed particle hydrodynamics (SPH) is a meshfree particle method based on Lagrangian formulation, and has been widely applied to different areas in engineering and science. This paper presents an overview on the SPH method and its recent developments, including (1) the need for meshfree particle methods, and advantages of SPH, (2) approximation schemes of the conventional SPH method and numerical techniques for deriving SPH formulations for partial differential equations such as the Navier-Stokes (N-S) equations, (3) the role of the smoothing kernel functions and a general approach to construct smoothing kernel functions, (4) kernel and particle consistency for the SPH method, and approaches for restoring particle consistency, (5) several important numerical aspects, and (6) some recent applications of SPH. The paper ends with some concluding remarks.

Smoothed Particle Hydrodynamics (SPH): an Overview and Recent Developments

This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms.Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises.Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation

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Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms

This article has presented an introductory tutorial on discontinuous dynamical systems. Various examples illustrate the pertinence of the continuity and Lipschitzness properties that guarantee the existence and uniqueness of classical solutions to ordinary differential equations. The lack of these properties in examples drawn from various disciplines motivates the need for more general notions than the classical one. First, we introduced notions of solution for discontinuous systems. Second, we reviewed the available tools from non- smooth analysis to study the gradient information of candidate Lyapunov functions. And, third, we presented nonsmooth stability tools to characterize the asymptotic behavior of solutions.

Discontinuous dynamical systems

We address the problem of covering an environment with robots equipped with sensors. The robots are heterogeneous in that the sensor footprints are different. Our work uses the location optimization framework in with three significant extensions. First, we consider robots with different sensor footprints, allowing, for example, aerial and ground vehicles to collaborate. We allow for finite size robots which enables implementation on real robotic systems. Lastly, we extend the previous work allowing for deployment in non convex environments.

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Sensing and coverage for a network of heterogeneous robots

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

/pdf/multi-uav-routing-for-area-coverage-and-remote-sensing-with-374phkuyqh.pdf

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

We develop a network of distributed mobile sensor systems as a solution to the emergency response problem. The mobile sensors are inside a building and they form a connected ad-hoc network. We discuss cooperative localization algorithms for these nodes. The sensors collect temperature data and run a distributed algorithm to assemble a temperature gradient. The mobile nodes are controlled to navigate using this temperature gradient. We also discuss how such networks can assist human users to find an exit. We have conducted an experiment to at a facility used to train firefighters to understand the environment and to test component technology. Results from experiments at this facility as well as simulations are presented here.

/pdf/distributed-search-and-rescue-with-robot-and-sensor-teams-14z9gc93lr.pdf

Distributed Search and Rescue with Robot and Sensor Teams

In this paper we address the problem of transporting objects with multiple mobile robots using the concept of “object closure”. In contrast to other manipulation techniques that are typically derived from form or force closure constraints, object closure requires the less stringent condition that the object be trapped or caged by the robots. Our basic goal in this paper is to develop decentralized control policies for a group of robots to move toward a goal position while maintaining a condition of object closure. We present experimental results that show polygonal mobile robots controlled using visual feedback, transporting a convex polygonal object in an obstacle free environment toward a prescribed goal.

http://www.cpdee.ufmg.br/~gpereira/papers/IJRR2004.pdf

Decentralized Algorithms for Multi-Robot Manipulation via Caging:

This paper presents a methodology for computation of artificial vector fields that allows a robot to converge to and circulate around generic curves specified in $n$ -dimensional spaces. These vector fields may be directly applied to solve several robot-navigation problems such as border monitoring, surveillance, target tracking, and multirobot pattern generation, with special application to fixed-wing aerial robots, which must keep a positive forward velocity and cannot converge to a single point. Unlike previous solutions found in the literature, the approach is based on fully continuous vector fields and is generalized to time-varying curves defined in $n$ -dimensional spaces. We provide mathematical proofs and present simulation and experimental results that illustrate the applicability of the proposed approach. We also present a methodology for construction of the target curve based on a given set of its samples.

/pdf/vector-fields-for-robot-navigation-along-time-varying-curves-4nhtaundg1.pdf

Guilherme A. S. Pereira

Papers

Sensing and coverage for a network of heterogeneous robots

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

Distributed Search and Rescue with Robot and Sensor Teams

Decentralized Algorithms for Multi-Robot Manipulation via Caging:

Vector Fields for Robot Navigation Along Time-Varying Curves in $n$ -Dimensions