Published in Annual Review of Control, Robotics, and Autonomous Systems
Equivariance is a common and natural property of many nonlinear control systems, especially those associated with models of mechatronic and navigation systems. Such systems admit a symmetry, associated with the equivariance, that provides structure enabling the design of robust and high-performance observers. A key insight is to pose the observer s...
Published in Annual Review of Control, Robotics, and Autonomous Systems
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 stabilizat...
Published in Annual Review of Control, Robotics, and Autonomous Systems
Internal models are nowadays customarily used in different domains of science and engineering to describe how living organisms or artificial computational units embed their acquired knowledge about recurring events taking place in the surrounding environment. This article reviews the internal model principle in control theory, bioengineering, and n...
Published in Annual Review of Control, Robotics, and Autonomous Systems
Planning under uncertainty is critical to robotics. The partially observable Markov decision process (POMDP) is a mathematical framework for such planning problems. POMDPs are powerful because of their careful quantification of the nondeterministic effects of actions and the partial observability of the states. But for the same reason, they are not...
Published in Annual Review of Control, Robotics, and Autonomous Systems
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....
Published in Annual Review of Control, Robotics, and Autonomous Systems
This article is an historical overview of control theory applied to robotic manipulators, with an emphasis on the early fundamental theoretical foundations of robot control. It discusses properties of robot dynamics that enable application of advanced control methods followed by robust and adaptive control of manipulators. It also discusses nonline...
Published in Annual Review of Control, Robotics, and Autonomous Systems
The dynamics of the turbulent atmospheric boundary layer play a fundamental role in wind farm energy production, governing the velocity field that enters the farm as well as the turbulent mixing that regenerates energy for extraction at downstream rows. Understanding the dynamic interactions among turbines, wind farms, and the atmospheric boundary ...
Published in Annual Review of Control, Robotics, and Autonomous Systems
This article provides a survey overview of the techniques, mechanisms, algorithms, and test and validation strategies required for the design of robotic grappling vehicles intended to approach and grapple free-flying client satellites. We concentrate on using a robotic arm to grapple a free-floating spacecraft, as distinct from spacecraft docking a...
Published in Annual Review of Control, Robotics, and Autonomous Systems
The last half decade has seen a steep rise in the number of contributions on safe learning methods for real-world robotic deployments from both the control and reinforcement learning communities. This article provides a concise but holistic review of the recent advances made in using machine learning to achieve safe decision-making under uncertaint...
Published in Annual Review of Control, Robotics, and Autonomous Systems
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 p...
