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.

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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.

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Recent Research in Cooperative Control of Multivehicle Systems

Two types of guidance systems are designed for a dual controlled missile having both forward control and tail control. The first type is an integrated single-loop guidance law, where the coupling between flight control and guidance loops is taken into account in the derivation process. The second type is an integrated two-loop autopilot-guidance law. In this case, the autopilot loop is designed separately from the guidance one, but all the states are fed-back into the guidance loop. It is demonstrated that the integrated two-loop autopilot-guidance law can manipulate the inner autopilot dynamics, resulting in the same performance as the integrated single-loop guidance law. The performance of the integrated two-loop autopilot-guidance diagram is shown to be highly dependent on the chosen autopilot block diagram.

Integrated single vs. two loop autopilot-guidance design for dual controlled missiles

A minimum effort intercept guidance algorithm is proposed for a missile that faces a group of potential targets and takes the decision to intercept one of the targets with a specified delay. The probability of the decision to engage either of the targets is assumed to be known. The algorithm is a linear combination of APN guidance algorithms for each of the targets. Numerical simulation results are presented.

Minimum Control Effort Guidance with Delayed Pursuit Decision

The process of integrating task and motion planning for unmanned aerial vehicles is examined. Here, an unmanned aerial vehicle is modeled as a Dubins vehicle: a vehicle with a minimum turn radius and the inability to go backward. Given a starting position and orientation for a Dubins vehicle and a set of stationary targets, the main problem is to determine the shortest yable path that visits each target. This problem is called the Dubins traveling salesman problem, an extension of the well-known traveling salesman problem. A number of algorithms with di erent approaches, including a hierarchical approach, a generalized traveling salesman problem reformulation approach, and a search with an upper bound Dubins cost approach, is developed and contrasted. Monte Carlo simulations were performed for a range of vehicle turn radii. Simulations results show that integrating two plausible kinematic satisfying paths as an upper bound to determine the cost-so-far into a search algorithm generally improves performance in terms of the shortest path cost and search complexity. Furthermore, when a suitable trajectory for traversing an ordered set of targets has been found, the applicability of using proportional navigation guidance is examined. It is shown that using a simple proportional navigation guidance law, stationary targets located within the vehicle's turn circle are unreachable. To address this issue, waypoints are generated that will allow the vehicle to reach these hard targets with minimum distance. The waypoints are generated by solving a relaxed version of the point to point Dubins problem. In addition, it is shown that any trajectory composed of point to point Dubins paths can be navigated using proportional navigation with a minimum number of waypoints, regardless of the target positions.

Integrating Task Assignment and Guidance via Motion Planning for Unmanned Aerial Vehicles

Trajectory planning and guidance are presented as successive steps in the process of solving problems related to the control of autonomous vehicles, with a focus on scenarios in which motion can be assumed to be planar. The exposition of relevant methods and results is structured in a manner that brings to the fore the principle of decomposing a given problem into subproblems whose solutions are analytically and computationally tractable, and can be synthesized to yield control algorithms amenable to real-time implementation. To this end, widely used kinematic models, for example, the Dubins and Reeds–Shepp vehicles, are presented and analyzed, along with more recent extensions thereof. Such models are useful abstractions, albeit not sufficiently granular to capture the complexities of real-world vehicles. Therefore, the analysis of the kinematic models is followed by methods for applying guidance laws that allow any vehicle that implements them to track the trajectories generated by means of the kinematic models within some margin of error. Trajectory planning and guidance are established and active research areas that are becoming increasingly interdisciplinary, especially in the context of autonomous systems; the list of references at the end of the chapter is intended as a complement to the necessarily selective choice of material presented herein.


Keywords:

autonomous vehicles;
Dubins and Reeds—Shepp models;
guidance;
guidance laws;
kinematic models;
path following;
trajectory planning

Trajectory Planning and Guidance

This paper considers the problem of emulating an optimal impact-angle-control guidance law using a pursuer guided with proportional navigation by using a virtual target approach. Based on the choice of the lead distance to the virtual targets, two algorithms for the virtual target computation are presented. In the first, the lead distance is specified in advance, whereas in the second, it is optimized. The simulation results demonstrate that the proposed solution can achieve an accurate emulation of the reference guidance law. 

Tal Shima

Papers

Integrated single vs. two loop autopilot-guidance design for dual controlled missiles

Minimum Control Effort Guidance with Delayed Pursuit Decision

Integrating Task Assignment and Guidance via Motion Planning for Unmanned Aerial Vehicles

Trajectory Planning and Guidance

Virtual Target Approach for Emulating Advanced Guidance Laws on Conventional Interceptors