Design and Control of Drones

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Mark W. Mueller ◽  
Seung Jae Lee ◽  
Raffaello D’Andrea
Keyword(s):  
Energy Consumption ◽  
Motion Planning ◽  
Recent Progress ◽  
Scaling Laws ◽  
Autonomous Systems ◽  
Annual Review ◽  
Publication Date ◽  
Trade Offs ◽  
Active Research ◽  
And Control

The design and control of drones remain areas of active research, and here we review recent progress in this field. In this article, we discuss the design objectives and related physical scaling laws, focusing on energy consumption, agility and speed, and survivability and robustness. We divide the control of such vehicles into low-level stabilization and higher-level planning such as motion planning, and we argue that a highly relevant problem is the integration of sensing with control and planning. Lastly, we describe some vehicle morphologies and the trade-offs that they represent. We specifically compare multicopters with winged designs and consider the effects of multivehicle teams. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Analysis and Control of Autonomous Mobility-on-Demand Systems

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Gioele Zardini ◽  
Nicolas Lanzetti ◽  
Marco Pavone ◽  
Emilio Frazzoli
Keyword(s):  
Performance Metrics ◽  
Transportation Systems ◽  
Demand Systems ◽  
Annual Review ◽  
Publication Date ◽  
Systematic Analysis ◽  
On Demand ◽  
Trade Offs ◽  
Autonomous Mobility ◽  
And Control

Challenged by urbanization and increasing travel needs, existing transportation systems need new mobility paradigms. In this article, we present the emerging concept of autonomous mobility-on-demand, whereby centrally orchestrated fleets of autonomous vehicles provide mobility service to customers. We provide a comprehensive review of methods and tools to model and solve problems related to autonomous mobility-on-demand systems. Specifically, we first identify problem settings for their analysis and control, from both operational and planning perspectives. We then review modeling aspects, including transportation networks, transportation demand, congestion, operational constraints, and interactions with existing infrastructure. Thereafter, we provide a systematic analysis of existing solution methods and performance metrics, highlighting trends and trade-offs. Finally, we present various directions for further research. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Model Reduction Methods for Complex Network Systems

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
X. Cheng ◽  
J.M.A. Scherpen
Keyword(s):  
Autonomous Systems ◽  
High Dimensional ◽  
Annual Review ◽  
Publication Date ◽  
Network Systems ◽  
Modeling And Control ◽  
Reduced Order ◽  
Reduction Methods ◽  
The Stability ◽  
And Control

Network systems consist of subsystems and their interconnections and provide a powerful framework for the analysis, modeling, and control of complex systems. However, subsystems may have high-dimensional dynamics and a large number of complex interconnections, and it is therefore relevant to study reduction methods for network systems. Here, we provide an overview of reduction methods for both the topological (interconnection) structure of a network and the dynamics of the nodes while preserving structural properties of the network. We first review topological complexity reduction methods based on graph clustering and aggregation, producing a reduced-order network model. Next, we consider reduction of the nodal dynamics using extensions of classical methods while preserving the stability and synchronization properties. Finally, we present a structure-preserving generalized balancing method for simultaneously simplifying the topological structure and the order of the nodal dynamics. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 3, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Asymptotically Optimal Sampling-Based Motion Planning Methods

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jonathan D. Gammell ◽  
Marlin P. Strub
Keyword(s):  
Motion Planning ◽  
Fundamental Problem ◽  
Autonomous Systems ◽  
Optimal Solution ◽  
Computational Effort ◽  
Annual Review ◽  
Publication Date ◽  
Ongoing Research ◽  
Asymptotically Optimal ◽  
Planning Methods

Motion planning is a fundamental problem in autonomous robotics that requires finding a path to a specified goal that avoids obstacles and takes into account a robot's limitations and constraints. It is often desirable for this path to also optimize a cost function, such as path length. Formal path-quality guarantees for continuously valued search spaces are an active area of research interest. Recent results have proven that some sampling-based planning methods probabilistically converge toward the optimal solution as computational effort approaches infinity. This article summarizes the assumptions behind these popular asymptotically optimal techniques and provides an introduction to the significant ongoing research on this topic. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Motion Control in Magnetic Microrobotics: From Individual and Multiple Robots to Swarms

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Lidong Yang ◽  
Li Zhang
Keyword(s):  
Motion Control ◽  
Autonomous Systems ◽  
System Structure ◽  
Future Research ◽  
Annual Review ◽  
Publication Date ◽  
Current Feedback ◽  
Loop Control ◽  
Planning And Control ◽  
And Control

Magnetic microrobotics has undergone approximately 20 years of development, and the robotics and control communities have contributed significant theoretical and practical results to the motion control aspects of this field. This article introduces fundamental motion principles covering individual, multiagent, and swarm control and critically reviews the state of the art along with representative results. It then describes closed-loop control (an important part of this field), including the system structure, current motion planning and control methods, and current feedback approaches. As the development of motion control in magnetic microrobotics is far from complete, especially for swarm control, its current limitations are discussed. Finally, we conclude with several challenges and future research directions. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 3, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Koopman Operators for Estimation and Control of Dynamical Systems

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Samuel E. Otto ◽  
Clarence W. Rowley
Keyword(s):  
Numerical Methods ◽  
Autonomous Systems ◽  
The State ◽  
Annual Review ◽  
Publication Date ◽  
Control Input ◽  
Koopman Operator ◽  
Estimation And Control ◽  
And Control ◽  
Theoretical Foundations

A common way to represent a system's dynamics is to specify how the state evolves in time. An alternative viewpoint is to specify how functions of the state evolve in time. This evolution of functions is governed by a linear operator called the Koopman operator, whose spectral properties reveal intrinsic features of a system. For instance, its eigenfunctions determine coordinates in which the dynamics evolve linearly. This review discusses the theoretical foundations of Koopman operator methods, as well as numerical methods developed over the past two decades to approximate the Koopman operator from data, for systems both with and without actuation. We pay special attention to ergodic systems, for which especially effective numerical methods are available. For nonlinear systems with an affine control input, the Koopman formalism leads naturally to systems that are bilinear in the state and the input, and this structure can be leveraged for the design of controllers and estimators. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Stability and Control of Power Grids

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Tao Liu ◽  
Yue Song ◽  
Lipeng Zhu ◽  
David J. Hill
Keyword(s):  
Critical Infrastructure ◽  
Autonomous Systems ◽  
Modern Society ◽  
Power Grids ◽  
Annual Review ◽  
Publication Date ◽  
New Paradigm ◽  
Stability And Control ◽  
The Stability ◽  
And Control

Power grids are critical infrastructure in modern society, and there are well-established theories for the stability and control of traditional power grids under a centralized paradigm. Driven by environmental and sustainability concerns, power grids are undergoing an unprecedented transition, with much more flexibility as well as uncertainty brought by the growing penetration of renewable energy and power electronic devices. A new paradigm for stability and control is under development that uses graph-based, data-based, and distributed analysis tools. This article surveys classic and novel results on the stability and control of power grids to provide a perspective on this both old and new subject. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Control as an Enabler for Electrified Mobility

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Andrew G. Alleyne ◽  
Christopher T. Aksland
Keyword(s):  
Online Publication ◽  
Autonomous Systems ◽  
Annual Review ◽  
Publication Date ◽  
Hierarchical Approach ◽  
Computationally Efficient ◽  
Physical Systems ◽  
The Third ◽  
Regulation And Tracking ◽  
And Control

This article outlines the importance of electrified mobility (e-mobility) in modern transport. One key goal of this review is to illustrate the role that control has played, and must continue to play, as e-mobility grows. The coordination of power in multiple modes (mechanical, electrical, and thermal) requires sophisticated controller algorithms. This review advocates for model-based approaches to control since there may not be readily available physical systems from which to gather data and do data-based control. A second goal of the article is to present methods for modeling these powertrain systems that are modular, scalable, flexible, and computationally efficient. A graph-based approach satisfies many of the desired criteria. The third goal is to review control approaches for these classes of systems and detail a hierarchical approach that makes trades across different domains of power. Optimization-based approaches are well suited to achieving the regulation and tracking goals, along with the minimization of costs and the satisfaction of constraints. Multiple examples, within this article and the references therein, support the presentation throughout. This field of e-mobility is rapidly growing, and control engineers are uniquely positioned to have an impact and lead many of the critical developments. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Cognitive Science as a Source of Forward and Inverse Models of Human Decisions for Robotics and Control

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Mark K. Ho ◽  
Thomas L. Griffiths
Keyword(s):  
Decision Making ◽  
Cognitive Science ◽  
Autonomous Systems ◽  
Annual Review ◽  
Publication Date ◽  
Statistical Machine Learning ◽  
Inverse Models ◽  
Control Research ◽  
Human Decision ◽  
And Control

Those designing autonomous systems that interact with humans will invariably face questions about how humans think and make decisions. Fortunately, computational cognitive science offers insight into human decision-making using tools that will be familiar to those with backgrounds in optimization and control (e.g., probability theory, statistical machine learning, and reinforcement learning). Here, we review some of this work, focusing on how cognitive science can provide forward models of human decision-making and inverse models of how humans think about others’ decision-making. We highlight relevant recent developments, including approaches that synthesize black box and theory-driven modeling, accounts that recast heuristics and biases as forms of bounded optimality, and models that characterize human theory of mind and communication in decision-theoretic terms. In doing so, we aim to provide readers with a glimpse of the range of frameworks, methodologies, and actionable insights that lie at the intersection of cognitive science and control research. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Integrated Task and Motion Planning

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Caelan Reed Garrett ◽  
Rohan Chitnis ◽  
Rachel Holladay ◽  
Beomjoon Kim ◽  
Tom Silver ◽  
...  
Keyword(s):  
Mathematical Programming ◽  
Motion Planning ◽  
Autonomous Systems ◽  
Annual Review ◽  
Publication Date ◽  
Continuous Space ◽  
Continuous Components ◽  
The World ◽  
Solution Methods ◽  
Discrete Task

The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning (TAMP). TAMP problems contain elements of discrete task planning, discrete–continuous mathematical programming, and continuous motion planning and thus cannot be effectively addressed by any of these fields directly. In this article, we define a class of TAMP problems and survey algorithms for solving them, characterizing the solution methods in terms of their strategies for solving the continuous-space subproblems and their techniques for integrating the discrete and continuous components of the search. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Animal-in-the-Loop: Using Interactive Robotic Conspecifics to Study Social Behavior in Animal Groups

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Tim Landgraf ◽  
Gregor H.W. Gebhardt ◽  
David Bierbach ◽  
Pawel Romanczuk ◽  
Lea Musiolek ◽  
...  
Keyword(s):  
Animal Behavior ◽  
Social Performance ◽  
Autonomous Systems ◽  
Annual Review ◽  
Publication Date ◽  
Animal Groups ◽  
Interdisciplinary Field ◽  
Technological Advances ◽  
Interaction Partners ◽  
And Control

Biomimetic robots that replace living social interaction partners can help elucidate the underlying interaction rules in animal groups. Our review focuses on the use of interactive robots that respond dynamically to animal behavior as part of a closed control loop. We discuss the most influential works to date and how they have contributed to our understanding of animal sociality. Technological advances permit the use of robots that can adapt to the situations they face and the conspecifics they encounter, or robots that learn to optimize their social performance from a set of experiences. We discuss how adaptation and learning may provide novel insights into group sociobiology and describe the technical challenges associated with these types of interactive robots. This interdisciplinary field provides a rich set of problems to be tackled by roboticists, machine learning engineers, and control theorists. By cultivating smarter robots, we can usher in an era of more nuanced exploration of animal behavior. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 3, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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