Bullo, Francesco
Overview
Works:  27 works in 68 publications in 1 language and 2,191 library holdings 

Genres:  Conference papers and proceedings Academic theses 
Roles:  Author, Editor 
Classifications:  TJ213, 629.8 
Publication Timeline
.
Most widely held works by
Francesco Bullo
Geometric control of mechanical systems : modeling, analysis, and design for simple mechanical control systems by
Francesco Bullo(
Book
)
13 editions published between 2005 and 2010 in English and held by 256 WorldCat member libraries worldwide
"Nonlinear control theoreticians will find explicit links between concepts in geometric mechanics and nonlinear control theory. Researchers in mechanics will find an overview of topics in control theory that have relevance to mechanics."Jacket
13 editions published between 2005 and 2010 in English and held by 256 WorldCat member libraries worldwide
"Nonlinear control theoreticians will find explicit links between concepts in geometric mechanics and nonlinear control theory. Researchers in mechanics will find an overview of topics in control theory that have relevance to mechanics."Jacket
Distributed control of robotic networks : a mathematical approach to motion coordination algorithms by
Francesco Bullo(
Book
)
15 editions published in 2009 in English and held by 158 WorldCat member libraries worldwide
This selfcontained 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 capabilitiesa
15 editions published in 2009 in English and held by 158 WorldCat member libraries worldwide
This selfcontained 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 capabilitiesa
Lagrangian and Hamiltonian methods for nonlinear control 2006 : proceedings from the 3rd IFAC workshop, Nagoya, Japan, July
2006 by IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control(
Book
)
12 editions published between 2006 and 2007 in English and held by 70 WorldCat member libraries worldwide
12 editions published between 2006 and 2007 in English and held by 70 WorldCat member libraries worldwide
Lagrangian and Hamiltonian methods for nonlinear control : proceedings from the 3rd IFAC Workshop, Nagoya, Japan, July 2006(
Book
)
3 editions published in 2007 in English and held by 11 WorldCat member libraries worldwide
3 editions published in 2007 in English and held by 11 WorldCat member libraries worldwide
Lagrangian and Hamiltonian Methods for Nonlinear Control 2006 by
Francesco Bullo(
Book
)
2 editions published in 2007 in English and held by 4 WorldCat member libraries worldwide
2 editions published in 2007 in English and held by 4 WorldCat member libraries worldwide
Nonlinear control of mechanical systems : a Riemannian geometry approach by
Francesco Bullo(
Book
)
1 edition published in 1999 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 1999 in English and held by 2 WorldCat member libraries worldwide
3rd IFAC Workshop on Distributed Estimation and Control in Networked Systems 2012 : Santa Barbara, California, USA, 1415
September 2012(
Book
)
1 edition published in 2013 in English and held by 2 WorldCat member libraries worldwide
1 edition published in 2013 in English and held by 2 WorldCat member libraries worldwide
Modeling and controllability for a class of hybrid mechanical systems by
Francesco Bullo(
)
2 editions published in 2002 in English and held by 2 WorldCat member libraries worldwide
2 editions published in 2002 in English and held by 2 WorldCat member libraries worldwide
Control and optimization in cooperative networks(
Book
)
1 edition published in 2009 in English and held by 1 WorldCat member library worldwide
1 edition published in 2009 in English and held by 1 WorldCat member library worldwide
On Vehicle Placement to Intercept Moving Targets (Preprint)(
Book
)
1 edition published in 2010 in English and held by 1 WorldCat member library worldwide
We address optimal placement of vehicles with simple motion, to intercept a mobile target that arrives stochastically on a line segment. The optimality of vehicle placement is measured through a cost function associated with intercepting the target. With a single vehicle, we assume that the target either moves with fixed speed and in a fixed direction or moves to maximize the vertical height or intercept time. We show that each of the corresponding cost functions is convex, has smooth gradient and has a unique minimizing location, and so the optimal vehicle placement is obtained by any standard gradientbased optimization technique. With multiple vehicles, we assume that the target moves with fixed speed and in fixed direction. We present a discrete time partitioning and gradientbased algorithm, and characterize conditions under which the algorithm asymptotically leads the vehicles to a set of critical configurations of the cost function
1 edition published in 2010 in English and held by 1 WorldCat member library worldwide
We address optimal placement of vehicles with simple motion, to intercept a mobile target that arrives stochastically on a line segment. The optimality of vehicle placement is measured through a cost function associated with intercepting the target. With a single vehicle, we assume that the target either moves with fixed speed and in a fixed direction or moves to maximize the vertical height or intercept time. We show that each of the corresponding cost functions is convex, has smooth gradient and has a unique minimizing location, and so the optimal vehicle placement is obtained by any standard gradientbased optimization technique. With multiple vehicles, we assume that the target moves with fixed speed and in fixed direction. We present a discrete time partitioning and gradientbased algorithm, and characterize conditions under which the algorithm asymptotically leads the vehicles to a set of critical configurations of the cost function
Kinematic controllability and motion planning for the snakeboard by
Francesco Bullo(
)
1 edition published in 2003 in English and held by 1 WorldCat member library worldwide
1 edition published in 2003 in English and held by 1 WorldCat member library worldwide
Constructive controllability algorithms for motion planning and optimization by W. Tood Cerven(
)
1 edition published in 2003 in English and held by 1 WorldCat member library worldwide
1 edition published in 2003 in English and held by 1 WorldCat member library worldwide
proportional derivative (PD) control on the euclidean group by
Francesco Bullo(
)
1 edition published in 1995 in English and held by 1 WorldCat member library worldwide
1 edition published in 1995 in English and held by 1 WorldCat member library worldwide
Adaptive and Distributed Algorithms for Vehicle Routing in a Stochastic and Dynamic Environment(
Book
)
1 edition published in 2010 in English and held by 1 WorldCat member library worldwide
In this paper we present adaptive and distributed algorithms for motion coordination of a group of m vehicles. The vehicles must service demands whose time of arrival, spatial location and service requirement are stochastic; the objective is to minimize the average time demands spend in the system. The general problem is known as the mvehicle Dynamic Traveling Repairman Problem (mDTRP). The best previously known control algorithms rely on centralized task assignment and are not robust against changes in the environment. In this paper, we first devise new control policies for the 1DTRP that: (i) are provably optimal both in lightload conditions (i.e., when the arrival rate for the demands is small) and in heavyload conditions (i.e., when the arrival rate for the demands is large), and (ii) are adaptive, in particular, they are robust against changes in load conditions. Then, we show that specific partitioning policies whereby the environment is partitioned among the vehicles and each vehicle follows a certain set of rules within its own region, are optimal in heavyload conditions. Building upon the previous results, we finally design control policies for the mDTRP that (i) are adaptive and distributed, and (ii) have strong performance guarantees in heavyload conditions and stabilize the system in any load condition
1 edition published in 2010 in English and held by 1 WorldCat member library worldwide
In this paper we present adaptive and distributed algorithms for motion coordination of a group of m vehicles. The vehicles must service demands whose time of arrival, spatial location and service requirement are stochastic; the objective is to minimize the average time demands spend in the system. The general problem is known as the mvehicle Dynamic Traveling Repairman Problem (mDTRP). The best previously known control algorithms rely on centralized task assignment and are not robust against changes in the environment. In this paper, we first devise new control policies for the 1DTRP that: (i) are provably optimal both in lightload conditions (i.e., when the arrival rate for the demands is small) and in heavyload conditions (i.e., when the arrival rate for the demands is large), and (ii) are adaptive, in particular, they are robust against changes in load conditions. Then, we show that specific partitioning policies whereby the environment is partitioned among the vehicles and each vehicle follows a certain set of rules within its own region, are optimal in heavyload conditions. Building upon the previous results, we finally design control policies for the mDTRP that (i) are adaptive and distributed, and (ii) have strong performance guarantees in heavyload conditions and stabilize the system in any load condition
On Optimal Sensor Placement and Motion Coordination for Target Tracking(
)
1 edition published in 2004 in English and held by 0 WorldCat member libraries worldwide
This work studies optimal sensor placement and motion coordination strategies for mobile sensor networks. For a target tracking application with range sensors, we investigate the determinant of the CramerRao Lower Bound and compute it in the 2D and 3D cases. We characterize the global minima of the 2D case. We propose and characterize motion coordination algorithms that steer the mobile sensor network to an optimal deployment and that are amenable to a decentralized implementation. Finally, our numerical simulations illustrate how the proposed motion coordination algorithms lead to the improved performance of an extended Kalman filter in a target tracking scenario
1 edition published in 2004 in English and held by 0 WorldCat member libraries worldwide
This work studies optimal sensor placement and motion coordination strategies for mobile sensor networks. For a target tracking application with range sensors, we investigate the determinant of the CramerRao Lower Bound and compute it in the 2D and 3D cases. We characterize the global minima of the 2D case. We propose and characterize motion coordination algorithms that steer the mobile sensor network to an optimal deployment and that are amenable to a decentralized implementation. Finally, our numerical simulations illustrate how the proposed motion coordination algorithms lead to the improved performance of an extended Kalman filter in a target tracking scenario
On DiscreteTime PursuitEvasion Games with Sensing Limitations(
)
1 edition published in 2008 in English and held by 0 WorldCat member libraries worldwide
We address discretetime pursuitevasion games in the plane where every player has identical sensing and motion ranges restricted to closed discs of given sensing and stepping radii. A single evader is initially located inside a bounded subset of the environment and does not move until detected. We propose a SweepPursuitCapture pursuer strategy to capture the evader and apply it to two variants of the game: the first involves a single pursuer and an evader in a bounded convex environment and the second involves multiple pursuers and an evader in a boundaryless environment. In the first game, we give a sufficient condition on the ratio of sensing to stepping radius of the players that guarantees capture. In the second, we determine the minimum probability of capture, which is a function of a novel pursuer formation and independent of the initial evader location. The Sweep and Pursuit phases reduce both games to previouslystudied problems with unlimited range sensing, and capture is achieved using available strategies. We obtain novel upper bounds on the capture time and present simulation studies that address the performance of the strategies under sensing errors, different ratios of sensing to stepping radius, greater evader speed and different number of pursuers
1 edition published in 2008 in English and held by 0 WorldCat member libraries worldwide
We address discretetime pursuitevasion games in the plane where every player has identical sensing and motion ranges restricted to closed discs of given sensing and stepping radii. A single evader is initially located inside a bounded subset of the environment and does not move until detected. We propose a SweepPursuitCapture pursuer strategy to capture the evader and apply it to two variants of the game: the first involves a single pursuer and an evader in a bounded convex environment and the second involves multiple pursuers and an evader in a boundaryless environment. In the first game, we give a sufficient condition on the ratio of sensing to stepping radius of the players that guarantees capture. In the second, we determine the minimum probability of capture, which is a function of a novel pursuer formation and independent of the initial evader location. The Sweep and Pursuit phases reduce both games to previouslystudied problems with unlimited range sensing, and capture is achieved using available strategies. We obtain novel upper bounds on the capture time and present simulation studies that address the performance of the strategies under sensing errors, different ratios of sensing to stepping radius, greater evader speed and different number of pursuers
Cooperative Networked Control of Dynamical PeertoPeer Vehicle Systems(
)
1 edition published in 2007 in English and held by 0 WorldCat member libraries worldwide
The goal of this MURI center was the development of a rigorous theoretical foundation, and scalable analytical tools and paradigms for construction of networked control for large numbers of autonomous and semiautonomous air vehicles. The research is specifically aimed at the critical reliability and performance issues facing autonomous vehicle systems which operate in highly uncertain environments, and enables the vehicles to form teams, manage information, and coordinate operations including deployment, task allocation and search. The program produced both the fundamental theory necessary to allow systematic performance analysis, verification and validation of such systems, as well as algorithms for implementation, and design software
1 edition published in 2007 in English and held by 0 WorldCat member libraries worldwide
The goal of this MURI center was the development of a rigorous theoretical foundation, and scalable analytical tools and paradigms for construction of networked control for large numbers of autonomous and semiautonomous air vehicles. The research is specifically aimed at the critical reliability and performance issues facing autonomous vehicle systems which operate in highly uncertain environments, and enables the vehicles to form teams, manage information, and coordinate operations including deployment, task allocation and search. The program produced both the fundamental theory necessary to allow systematic performance analysis, verification and validation of such systems, as well as algorithms for implementation, and design software
Monitoring Environmental Boundaries with a Robotic Sensor Network(
)
1 edition published in 2006 in English and held by 0 WorldCat member libraries worldwide
In this paper, we propose and analyze two algorithms to monitor an environmental boundary with mobile sensors. The objective is to optimally approximate the boundary with a polygon. In the first scenario the mobile sensors know the boundary and the approximating polygon is defined by the sensors' positions. In the second scenario the mobile sensors rely only on sensed local information to position some interpolation points and define an approximating polygon. For both scenarios we design algorithms that distribute the vertices of the approximating polygon uniformly along the boundary. The notion of uniform placement relies on a metric inspired by known results on approximation of convex bodies. The first algorithm is proved to converge in the case of static boundaries whereas the second one is provably convergent also for slowlymoving boundaries because of certain inputtostate stability properties
1 edition published in 2006 in English and held by 0 WorldCat member libraries worldwide
In this paper, we propose and analyze two algorithms to monitor an environmental boundary with mobile sensors. The objective is to optimally approximate the boundary with a polygon. In the first scenario the mobile sensors know the boundary and the approximating polygon is defined by the sensors' positions. In the second scenario the mobile sensors rely only on sensed local information to position some interpolation points and define an approximating polygon. For both scenarios we design algorithms that distribute the vertices of the approximating polygon uniformly along the boundary. The notion of uniform placement relies on a metric inspired by known results on approximation of convex bodies. The first algorithm is proved to converge in the case of static boundaries whereas the second one is provably convergent also for slowlymoving boundaries because of certain inputtostate stability properties
Trajectories for Locomotion Systems: A Geometric and Computational Approach via Series Expansions(
)
1 edition published in 2004 in English and held by 0 WorldCat member libraries worldwide
The objective of this research has been the design and validation of innovative methods for motion planning of highly mobile allterrain vehicles and motion coordination for multivehicle networks. The initial focus of this research was on algorithms for (single) vehicle trajectory generation. We have studies fast local trajectory optimization algorithms for vehicles with limited control authority. The main research focus has been on a novel class of asynchronous distributed coordination algorithms for multivehicle networks. We have developed coverage and coordination algorithms for communicationconstrained vehicle models. The algorithms are spatially distributed in the sense that only spatially localized information is required for their implementation. We believe this is a fundamental improvement over the current stateoftheart in motion coordination. Finally, we have developed an outdoor experimental platform, called the MultiRover Network Laboratory," consisting of eight model rovers equipped with embedded computers, wifeless interfaces, and sensors
1 edition published in 2004 in English and held by 0 WorldCat member libraries worldwide
The objective of this research has been the design and validation of innovative methods for motion planning of highly mobile allterrain vehicles and motion coordination for multivehicle networks. The initial focus of this research was on algorithms for (single) vehicle trajectory generation. We have studies fast local trajectory optimization algorithms for vehicles with limited control authority. The main research focus has been on a novel class of asynchronous distributed coordination algorithms for multivehicle networks. We have developed coverage and coordination algorithms for communicationconstrained vehicle models. The algorithms are spatially distributed in the sense that only spatially localized information is required for their implementation. We believe this is a fundamental improvement over the current stateoftheart in motion coordination. Finally, we have developed an outdoor experimental platform, called the MultiRover Network Laboratory," consisting of eight model rovers equipped with embedded computers, wifeless interfaces, and sensors
Notes on Averaging Over Acyclic Digraphs and Discrete Coverage Control(
)
1 edition published in 2006 in English and held by 0 WorldCat member libraries worldwide
In this paper, we show the relationship between two algorithms and optimization problems that are the subject of recent attention in the networking and control literature. First, we obtain some results on averaging algorithms over acyclic digraphs with fixed and controlledswitching topology. Second, we discuss continuous and discrete coverage control laws. Further, we show how discrete coverage control laws can be cast as averaging algorithms defined over an appropriate graph that we term the discrete Voronoi graph
1 edition published in 2006 in English and held by 0 WorldCat member libraries worldwide
In this paper, we show the relationship between two algorithms and optimization problems that are the subject of recent attention in the networking and control literature. First, we obtain some results on averaging algorithms over acyclic digraphs with fixed and controlledswitching topology. Second, we discuss continuous and discrete coverage control laws. Further, we show how discrete coverage control laws can be cast as averaging algorithms defined over an appropriate graph that we term the discrete Voronoi graph
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