Energy-Aware Controllability of Complex Networks

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Giacomo Baggio ◽  
Fabio Pasqualetti ◽  
Sandro Zampieri
Keyword(s):  
Complex Networks ◽  
Autonomous Systems ◽  
Random Networks ◽  
Annual Review ◽  
Publication Date ◽  
Energy Aware ◽  
Control Effort ◽  
Linear Dynamics ◽  
Introductory Overview ◽  
Engineering Sciences

Understanding the fundamental principles and limitations of controlling complex networks is of paramount importance across natural, social, and engineering sciences. The classic notion of controllability does not capture the effort needed to control dynamical networks, and quantitative measures of controllability have been proposed to remedy this problem. This article presents an introductory overview of the practical (i.e., energy-related) aspects of controlling networks governed by linear dynamics. First, we introduce a class of energy-aware controllability metrics and discuss their properties. Then, we establish bounds on these metrics, which allow us to understand how the structure of the network impacts the control energy. Finally, we examine the problem of optimally selecting a set of control nodes so as to minimize the control effort, and compare the performance of some simple strategies to approximately solve this problem. Throughout the article, we include examples of structured and random networks to illustrate our results. 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.

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.

Secure Networked Control Systems

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Henrik Sandberg ◽  
Vijay Gupta ◽  
Karl H. Johansson
Keyword(s):  
Control Systems ◽  
Critical Infrastructure ◽  
Networked Control Systems ◽  
Denial Of Service ◽  
Autonomous Systems ◽  
Mitigation Strategies ◽  
Networked Control ◽  
Annual Review ◽  
Publication Date ◽  
Process Industries

Cyber-vulnerabilities are being exploited in a growing number of control systems. As many of these systems form the backbone of critical infrastructure and are becoming more automated and interconnected, it is of the utmost importance to develop methods that allow system designers and operators to do risk analysis and develop mitigation strategies. Over the last decade, great advances have been made in the control systems community to better understand cyber-threats and their potential impact. This article provides an overview of recent literature on secure networked control systems. Motivated by recent cyberattacks on the power grid, connected road vehicles, and process industries, a system model is introduced that covers many of the existing research studies on control system vulnerabilities. An attack space is introduced that illustrates how adversarial resources are allocated in some common attacks. The main part of the article describes three types of attacks: false data injection, replay, and denial-of-service attacks. Representative models and mathematical formulations of these attacks are given along with some proposed mitigation strategies. The focus is on linear discrete-time plant models, but various extensions are presented in the final section, which also mentions some interesting research problems for future work. 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.

Stimuli-Responsive Polymers for Soft Robotics

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Yusen Zhao ◽  
Mutian Hua ◽  
Yichen Yan ◽  
Shuwang Wu ◽  
Yousif Alsaid ◽  
...  
Keyword(s):  
Autonomous Systems ◽  
Soft Robotics ◽  
Annual Review ◽  
Liquid Crystal Polymers ◽  
Publication Date ◽  
Stimuli Responsive ◽  
Stimuli Responsive Polymers ◽  
Responsive Polymers ◽  
Evaluation Of Performance ◽  
Robotic Applications

This article reviews recent progress in the use of stimuli-responsive polymers for soft robotics. First, we introduce different types of representative stimuli-responsive polymers, which include liquid crystal polymers and elastomers, hydrogels, shape memory polymers, magnetic elastomers, electroactive polymers, and thermal expansion actuators. We focus on the mechanisms of actuation and the evaluation of performance and discuss strategies for improvements. We then present examples of soft robotic applications based on stimuli-responsive polymers for bending, grasping, walking, swimming, flying, and sensing control. Finally, we discuss current opportunities and challenges of stimuli-responsive soft robots for future study. 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.

Methods for Robot Behavior Adaptation for Cognitive Neurorehabilitation

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Alyssa Kubota ◽  
Laurel D. Riek
Keyword(s):  
State Of The Art ◽  
Cognitive Impairments ◽  
Autonomous Systems ◽  
Behavioral Adaptation ◽  
Annual Review ◽  
Publication Date ◽  
Pharmacological Treatments ◽  
Robot Behavior ◽  
Behavioral Treatments ◽  
Physical Abilities

An estimated 11% of adults report experiencing some form of cognitive decline, which may be associated with conditions such as stroke or dementia and can impact their memory, cognition, behavior, and physical abilities. While there are no known pharmacological treatments for many of these conditions, behavioral treatments such as cognitive training can prolong the independence of people with cognitive impairments. These treatments teach metacognitive strategies to compensate for memory difficulties in their everyday lives. Personalizing these treatments to suit the preferences and goals of an individual is critical to improving their engagement and sustainment, as well as maximizing the treatment's effectiveness. Robots have great potential to facilitate these training regimens and support people with cognitive impairments, their caregivers, and clinicians. This article examines how robots can adapt their behavior to be personalized to an individual in the context of cognitive neurorehabilitation. We provide an overview of existing robots being used to support neurorehabilitation and identify key principles for working in this space. We then examine state-of-the-art technical approaches for enabling longitudinal behavioral adaptation. To conclude, we discuss our recent work on enabling social robots to automatically adapt their behavior and explore open challenges for longitudinal behavior adaptation. This work will help guide the robotics community as it continues to provide more engaging, effective, and personalized interactions between people and robots. 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 Set Propagation Techniques for Reachability Analysis

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Matthias Althoff ◽  
Goran Frehse ◽  
Antoine Girard
Keyword(s):  
Hybrid Systems ◽  
Fundamental Problem ◽  
Autonomous Systems ◽  
Reachability Analysis ◽  
Controller Synthesis ◽  
Annual Review ◽  
Publication Date ◽  
Initial States ◽  
Set Of Initial States ◽  
Real World Problems

Reachability analysis consists in computing the set of states that are reachable by a dynamical system from all initial states and for all admissible inputs and parameters. It is a fundamental problem motivated by many applications in formal verification, controller synthesis, and estimation, to name only a few. This article focuses on a class of methods for computing a guaranteed overapproximation of the reachable set of continuous and hybrid systems, relying predominantly on set propagation; starting from the set of initial states, these techniques iteratively propagate a sequence of sets according to the system dynamics. After a review of set representation and computation, the article presents the state of the art of set propagation techniques for reachability analysis of linear, nonlinear, and hybrid systems. It ends with a discussion of successful applications of reachability analysis to real-world problems. 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 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.

Noninvasive Brain–Machine Interfaces for Robotic Devices

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Luca Tonin ◽  
José del R. Millán
Keyword(s):  
Autonomous Systems ◽  
Discrete Control ◽  
Annual Review ◽  
Publication Date ◽  
User Centered Design ◽  
Brain Machine Interfaces ◽  
Motor Disabilities ◽  
Severe Motor ◽  
Robotic Devices ◽  
And Robotics

The last decade has seen a flowering of applications driven by brain–machine interfaces (BMIs), particularly brain-actuated robotic devices designed to restore the independence of people suffering from severe motor disabilities. This review provides an overview of the state of the art of noninvasive BMI-driven devices based on 86 studies published in the last 15 years, with an emphasis on the interactions among the user, the BMI system, and the robot. We found that BMIs are used mostly to drive devices for navigation (e.g., telepresence mobile robots), with BMI paradigms based mainly on exogenous stimulation, and the majority of brain-actuated robots adopt a discrete control strategy. Most critically, in only a few works have disabled people evaluated a brain-actuated robot. The review highlights the most urgent challenges in the field, from the integration between BMI and robotics to the need for a user-centered design to boost the translational impact of BMIs. 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.

Mechanisms for Robotic Grasping and Manipulation

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Vincent Babin ◽  
Clément Gosselin
Keyword(s):  
Online Publication ◽  
Autonomous Systems ◽  
Robotic Manipulation ◽  
Annual Review ◽  
Publication Date ◽  
Robotic Grasping ◽  
Grasp Planning ◽  
Grasping And Manipulation

This article reviews the literature on the design of robotic mechanical grippers, with a focus on the mechanical aspects, which are believed to be the main bottleneck for effective designs. Our discussion includes gripper architectures and means of actuation, anthropomorphism and grasp planning, and robotic manipulation, emphasizing the complementary concepts of intrinsic and extrinsic dexterity. We also consider interactions of robotic grippers with the environment and with the objects to be grasped and argue that the proper handling of such interactions is key to the development of grasping and manipulation tools and scenarios. Finally, we briefly present examples of recent designs to support the discussion. 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 Autonomy in Surgical Robotics

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Aleks Attanasio ◽  
Bruno Scaglioni ◽  
Elena De Momi ◽  
Paolo Fiorini ◽  
Pietro Valdastri
Keyword(s):  
Online Publication ◽  
Autonomous Systems ◽  
Surgical Robotics ◽  
Annual Review ◽  
Publication Date ◽  
Surgical Robots ◽  
Level 3 ◽  
Level 1 ◽  
Level 2 ◽  
Task Level

This review examines the dichotomy between automatic and autonomous behaviors in surgical robots, maps the possible levels of autonomy of these robots, and describes the primary enabling technologies that are driving research in this field. It is organized in five main sections that cover increasing levels of autonomy. At level 0, where the bulk of commercial platforms are, the robot has no decision autonomy. At level 1, the robot can provide cognitive and physical assistance to the surgeon, while at level 2, it can autonomously perform a surgical task. Level 3 comes with conditional autonomy, enabling the robot to plan a task and update planning during execution. Finally, robots at level 4 can plan and execute a sequence of surgical tasks autonomously. 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.

Sign in / Sign up

Export Citation Format

Share Document