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1. Active Learning of Dynamics for Data-Driven Control Using Koopman Operators

   https://doi.org/10.1109/TRO.2019.2923880  

   Abraham, Ian; Murphey, Todd D. (July 2019, IEEE Transactions on Robotics)

   This paper presents an active learning strategy for robotic systems that takes into account task information, enables fast learning, and allows control to be readily synthesized by taking advantage of the Koopman operator representation. We first motivate the use of representing nonlinear systems as linear Koopman operator systems by illustrating the improved model-based control performance with an actuated Van der Pol system. Information-theoretic methods are then applied to the Koopman operator formulation of dynamical systems where we derive a controller for active learning of robot dynamics. The active learning controller is shown to increase the rate of information about the Koopman operator. In addition, our active learning controller can readily incorporate policies built on the Koopman dynamics, enabling the benefits of fast active learning and improved control. Results using a quadcopter illustrate single-execution active learning and stabilization capabilities during free-fall. The results for active learning are extended for automating Koopman observables and we implement our method on real robotic systems. 

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2. Programming and simulating chemical reaction networks on a surface

   https://doi.org/10.1098/rsif.2019.0790  

   Clamons, Samuel; Qian, Lulu; Winfree, Erik (May 2020, Journal of The Royal Society Interface)

   Models of well-mixed chemical reaction networks (CRNs) have provided a solid foundation for the study of programmable molecular systems, but the importance of spatial organization in such systems has increasingly been recognized. In this paper, we explore an alternative chemical computing model introduced by Qian & Winfree in 2014, the surface CRN, which uses molecules attached to a surface such that each molecule only interacts with its immediate neighbours. Expanding on the constructions in that work, we first demonstrate that surface CRNs can emulate asynchronous and synchronous deterministic cellular automata and implement continuously active Boolean logic circuits. We introduce three new techniques for enforcing synchronization within local regions, each with a different trade-off in spatial and chemical complexity. We also demonstrate that surface CRNs can manufacture complex spatial patterns from simple initial conditions and implement interesting swarm robotic behaviours using simple local rules. Throughout all example constructions of surface CRNs, we highlight the trade-off between the ability to precisely place molecules and the ability to precisely control molecular interactions. Finally, we provide a Python simulator for surface CRNs with an easy-to-use web interface, so that readers may follow along with our examples or create their own surface CRN designs. 

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3. Perception-Motion Coupling in Active Telepresence: Human Behavior and Teleoperation Interface Design

   https://doi.org/10.1145/3571599  

   Lin, Tsung-Chi; Unni Krishnan, Achyuthan; Li, Zhi (September 2023, ACM Transactions on Human-Robot Interaction)

   Teleoperation enables complex robot platforms to perform tasks beyond the scope of the current state-of-the-art robot autonomy by imparting human intelligence and critical thinking to these operations. For seamless control of robot platforms, it is essential to facilitate optimal situational awareness of the workspace for the operator through active telepresence cameras. However, the control of these active telepresence cameras adds an additional degree of complexity to the task of teleoperation. In this paper we present our results from the user study that investigates: (1) how the teleoperator learns or adapts to performing the tasks via active cameras modeled after camera placements on the TRINA humanoid robot; (2) the perception-action coupling operators implement to control active telepresence cameras, and (3) the camera preferences for performing the tasks. These findings from the human motion analysis and post-study survey will help us determine desired design features for robot teleoperation interfaces and assistive autonomy. 

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4. Strain-Actuated Solar Arrays for Spacecraft Attitude Control Assisted by Viscoelastic Damping

   Yong Hoon Lee, Vedant (May 2019, 13th World Congress of Structural and Multidisciplinary Optimization)

   This article presents a utilization of viscoelastic damping to reduce control system complexity for strain-actuated solar array (SASA) based spacecraft attitude control systems (ACSs). SASA utilizes intelligent structures for attitude control, and is a promising next-generation spacecraft ACS technology with the potential to achieve unprecedented levels of pointing accuracy and jitter reduction during key scientific observation periods. The current state-of-the-art SASA implementation utilizes piecewise modeling of distributed piezoelectric (PZT) actuators, resulting in a monolithic structure with the potential for enhanced ACS reliability. PZT actuators can operate at high frequencies, which enables active vibration damping to achieve ultra-quiet operation for sensitive instruments. Relying on active damping alone, however, requires significant control system complexity, which has so far limited adoption of intelligent structures in spacecraft control systems. Here we seek to understand how to modify passive system design in strategic ways to reduce control system complexity while maintaining high performance. An integrated physical and control system design (codesign) optimization strategy is employed to ensure system-optimal performance, and to help understand design coupling between passive physical aspects of design and active control system design. In this study, we present the possibility of utilizing viscoelastic material distributed throughout the SASA substructure to provide tailored passive damping, intending to reduce control system complexity. At this early phase of study, the effect of temperature variation on material behavior is not considered; the study focuses instead on the design coupling between distributed material and control systems. The spatially-distributed design of both elastic and viscoelastic material in the SASA substructure is considered in an integrated manner. An approximate model is used that balances predictive accuracy and computational efficiency. This model approximates the distributed compliant SASA structure using a series of rigid links connected by generalized torsional springs and dampers. This multi-link pseudo-rigid-body dynamic model (PRBDM) with lumped viscoelastic damping models is derived, and is used in numerical co-design studies to quantify the tradeoffs and benefits of using distributed passive damping to reduce the complexity of SASA control systems. 

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5. Why Didn’t You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models

   https://doi.org/10.18653/v1/P19-1637  

   Kumar, Varun; Smith-Renner, Alison; Findlater, Leah; Seppi, Kevin; Boyd-Graber, Jordan (January 2019, Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics)

   null (Ed.)

   To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments. These approaches extend previously proposed frameworks, including constraints and informed prior-based methods. Users should have a sense of control in HLTM systems, so we propose a control metric to measure whether refinement operations’ results match users’ expectations. Informed prior-based methods provide better control than constraints, but constraints yield higher quality topics. 

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