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

This paper reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles, and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

/pdf/an-overview-of-recent-progress-in-the-study-of-distributed-1xnb6e12se.pdf

An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination

This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination

This is the fifth part of a series of papers that provide a comprehensive survey of techniques for tracking maneuvering targets without addressing the so-called measurement-origin uncertainty. Part I and Part II deal with target motion models. Part III covers measurement models and associated techniques. Part IV is concerned with tracking techniques that are based on decisions regarding target maneuvers. This part surveys the multiple-model methods $the use of multiple models (and filters) simultaneously - which is the prevailing approach to maneuvering target tracking in recent years. The survey is presented in a structured way, centered around three generations of algorithms: autonomous, cooperating, and variable structure. It emphasizes the underpinning of each algorithm and covers various issues in algorithm design, application, and performance.

Survey of maneuvering target tracking. Part V. Multiple-model methods

This paper presents a survey of recent research in cooperative control of multivehicle systems, using a common mathematical framework to allow different methods to be described in a unified way. The survey has three primary parts: an overview of current applications of cooperative control, a summary of some of the key technical approaches that have been explored, and a description of some possible future directions for research. Specific technical areas that are discussed include formation control, cooperative tasking, spatiotemporal planning, and consensus.

/pdf/recent-research-in-cooperative-control-of-multivehicle-4aw1z97kwj.pdf

Recent Research in Cooperative Control of Multivehicle Systems

In this paper, the problem of robust trajectory tracking by a multicopter platform is formulated as a linear-quadratic differential game against unknown external disturbances (nature). The desired trajectory is composed of position and yaw constraint, which is known to be a differentially flat output for multicopter state dynamics. Using this property, a linearized error dynamics is obtained in the vicinity of the nominal states and the nominal control inputs. To avoid singularities, the linearized error dynamics is derived using quaternion representation. Based on it, an optimal saddle point strategy for trajectory tracking is presented, where controller gains are calculated \textit{apriori} by numerically solving a differential Ricatti equation. A salient feature of this control design is that both the position and the attitude control loops are integrated, and there are only two tuning parameters — one corresponding to the tradeoff between control effort and tracking accuracy and the other corresponding to robustness. Simulations as well as experimental validations are presented to demonstrate the performance and applicability of the controller. 

Robust Trajectory Tracking by a Multicopter Platform: A Game Against Nature

This paper presents a guidance algorithm for a pursuer in a many-on-many intercept scenario that includes the possibility of dynamic weapon–target (re)assignment based on a simple target priority scheme. Given the probabilities of success of each preceding pursuer against each possible evading target, a guidance algorithm is designed that provides minimum average quadratic effort over all the possible outcomes of the engagements that may take place during the time of flight. The result is a guidance algorithm in the form of a linear combination of (augmented) proportional navigation guidance terms with time-varying weights. Effectively, this is a one-against-many guidance law. An efficient algorithm for the implementation of the guidance law is presented, and numerical simulations based on the nonlinear equations of motion are used to demonstrate its performance. 

Minimum Effort Pursuit Guidance with Multiple Delayed Engagement Decisions

Single vs. Two-Loop Full-State Multi-Input Multi-Output Missile Guidance

Linear Quadratic Optimal Cooperative Strategies for Active Aircraft Protection

A differential game based strategy, L2/L∞ guidance law, is derived for a missile with large lateral acceleration capability intercepting an evading target which has limited lateral acceleration capability. Planar motion, linearized kinematics, arbitrary-order linear adversaries' dynamics, and perfect information are assumed. The engagement is formulated as a two-person zero-sum pursuit-evasion game with a linear quadratic cost, where only the maneuverability of the evader is assumed bounded. The open loop solution is derived via direct derivation of the game's lower and upper values and the saddle point condition. It is shown that the existence of an open loop saddle point solution depends on the engagement's initial conditions. A closed form guidance law is formulated, consisting of the optimal saddle point strategies and three proposed variants when no saddle point solution exists. Linear simulations are performed for the case of a pursuer with first order control dynamics and an evader with zero-lag dynamics, in order to illustrate the L2/L∞ guidance law's implementation benefits and performance in comparison with a classical optimal guidance law.

Tal Shima

Papers

Robust Trajectory Tracking by a Multicopter Platform: A Game Against Nature

Minimum Effort Pursuit Guidance with Multiple Delayed Engagement Decisions

Single vs. Two-Loop Full-State Multi-Input Multi-Output Missile Guidance

Linear Quadratic Optimal Cooperative Strategies for Active Aircraft Protection

A mixed L2/L∞ differential game approach to pursuit-evasion guidance