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Accurately parameterizing human gait cycles is crucial for developing control systems for lower-limb wearable robots. Previous studies on characterizing human gait cycle investigated the use of human-inspired phase variables, but they lack robustness and adaptability to accommodate for transitions that occur between locomotor tasks. This paper proposes augmenting the traditional phase variables with a canonical dynamical system. This system considers the differences between the estimated and true thigh angular velocities, based on which the Fourier series coefficients and phase information will be dynamically updated via an adaptive frequency oscillator. Experiments with six able-bodied participants on level ground, inclines, and declines walking show that the augmented phase variable adapts to various locomotor tasks and transitions better than the traditional approach. 

Yoshimura origami is a classical folding pattern that has inspired many deployable structure designs. Its applications span from space exploration, kinetic architectures and soft robots to even everyday household items. However, despite its wide usage, Yoshimura has been fixated on a set of design constraints to ensure its flat foldability. Through extensive kinematic analysis and prototype tests, this study presents a new Yoshimura that intentionally defies these constraints. Remarkably, one can impart a unique meta-stability by using the Golden Ratio angle ( ${\cot }^{-1}1.618\approx {31.72}^{\circ }$) to define the triangular facets of a generalized Yoshimura (with $n=3$, where $n$is the number of rhombi shapes along its cylindrical circumference). As a result, when its facets are strategically popped out, a ‘Golden Ratio Yoshimura’ boom with $m$modules can be theoretically reconfigured into $8^m$geometrically unique and load-bearing shapes. This result not only challenges the existing design norms but also opens up a new avenue to create deployable and versatile structural systems. This article is part of the theme issue ‘Origami/Kirigami-inspired structures: from fundamentals to applications’. 

Coastal dunes are globally recognized as natural features that can enhance coastal resilience and protection from wave events, storm surges, coastal flooding, and longer- term sea level rise. As a result, dune restoration is being increasingly used along urban and natural coasts as an adaptation option for climate change. However, information on the performance of restored dunes in response to extreme events is limited. On urban beaches where management includes grooming, dunes are often degraded or absent, leaving coastal communities more vulnerable to flooding and erosion during storms and wave events. Following an extreme wave surge event in December 2023, we compared the performance of a small (1.2 hectare) pilot dune restoration on an intensively groomed urban beach in southern California to an adjacent mechanically groomed control site. We used total water level (wave setup, tide, wave runup) as a proxy for flooding potential. The average wave runup incursion distance was extended 13.6 m farther inland on the groomed control site compared to the dune restoration site. This result demonstrates the potential for restored dunes to enhance flood protection and the potential for increasing coastal resilience using nature-based solutions on urban beaches. 

We discuss novel human-centered intelligent spaces, specifically robotic elements which form the core of an interactive room that physically reconfigures: a robot-room. The proposed robot-room represents an advance in human-centered computing whereby human interaction is within a machine that physically envelops us. We discuss the motivation for such robot-rooms, and present initial work aimed at their physical realization. 

The addition of geometric reconfigurability in a cable driven parallel robot (CDPR) introduces kinematic redundancies which can be exploited for manipulating structural and mechanical properties of the robot through redundancy resolution. In the event of a cable failure, a reconfigurable CDPR (rCDPR) can also realign its geometric arrangement to overcome the effects of cable failure and recover the original expected trajectory and complete the trajectory tracking task. In this paper we discuss a fault tolerant control (FTC) framework that relies on an Interactive Multiple Model (IMM) adaptive estimation filter for simultaneous fault detection and diagnosis (FDD) and task recovery. The redundancy resolution scheme for the kinematically redundant CDPR takes into account singularity avoidance, manipulability and wrench quality maximization during trajectory tracking. We further introduce a trajectory tracking methodology that enables the automatic task recovery algorithm to consistently return to the point of failure. This is particularly useful for applications where the planned trajectory is of greater importance than the goal positions, such as painting, welding or 3D printing applications. The proposed control framework is validated in simulation on a planar rCDPR with elastic cables and parameter uncertainties to introduce modeled and unmodeled dynamics in the system as it tracks a complete trajectory despite the occurrence of multiple cable failures. As cables fail one by one, the robot topology changes from an over-constrained to a fully constrained and then an under-constrained CDPR. The framework is applied with a constant-velocity kinematic feedforward controller which has the advantage of generating steady-state inputs despite dynamic oscillations during cable failures, as well as a Linear Quadratic Regulator (LQR) feedback controller to locally dampen these oscillations. 

Compliant grasping is crucial for secure handling objects not only vary in shapes but also in mechanical properties. We propose a novel soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers conform to object shapes facilitating the handling of objects of different types, shapes, and sizes. Each soft gripper finger has a length constraining mechanism (an articulable rigid backbone) and is powered by pneumatic muscle actuators. We derive the kinematic model of the gripper and use an empirical approach to simultaneously map input pressures to stiffness control and bending deformation of fingers. We use these mappings to demonstrate decoupled stiffness and shape (bending) control of various grasping configurations. We conduct tests to quantify the grip quality when holding objects as the gripper changes orientation, the ability to maintain the grip as the gripper is subjected to translational and rotational movements, and the external force perturbations required to release the object from the gripper under various stiffness and shape (bending) settings. The results validate the proposed gripper's performance and show how the decoupled stiffness and shape control can improve the grasping quality in soft robotic grippers. 

This dataset includes chironomid species assemblage data and air temperature estimates from 400+ lakes across northern North America, Greenland, Iceland, and Svalbard to inform interpretations of Holocene subfossil chironomid assemblages used in paleolimnological reconstruction. This calibration-set was developed by re-identifying and taxonomically harmonizing chironomids in previously described surface sediment samples, with identifications made at finer taxonomic resolution than in original publications (which are cited in the publication describing this dataset, Medeiros et al. 2022 Quaternary Science Reviews, and should be cited by dataset users). Site summer air temperatures are newly estimated with a consistent method using the WorldClim 2.1 gridded bioclimatic dataset. The large geographic coverage of this dataset is intended to provide climatic analogs for a wide range of Holocene climates in the northwest North Atlantic region and North American Arctic, including Greenland. For many of these regions, modern calibration data for paleoclimate proxies are sparse despite keen interest in paleoclimate reconstructions from high latitudes. Dataset users should consult and cite the following source publication: Medeiros, A.S., Chipman, M., Francis, D.R., Hamerlik, L., Langdon, P., Puleo, P.J.K., Schellinger, G., Steigleder, R., Walker, I.R., Woodroffe, S., and Axford, Y. 2022. A continent-scale chironomid training set for reconstructing arctic temperatures. Quaternary Science Reviews 294, 107728. DOI 10.1016/j.quascirev.2022.107728.