Search for: All records

Abstract PremisePteridophytes—vascular land plants that disperse by spores—are a powerful system for studying plant evolution, particularly with respect to the impact of abiotic factors on evolutionary trajectories through deep time. However, our ability to use pteridophytes to investigate such questions—or to capitalize on the ecological and conservation‐related applications of the group—has been impaired by the relative isolation of the neo‐ and paleobotanical research communities and by the absence of large‐scale biodiversity data sources. MethodsHere we present the Pteridophyte Collections Consortium (PCC), an interdisciplinary community uniting neo‐ and paleobotanists, and the associated PteridoPortal, a publicly accessible online portal that serves over three million pteridophyte records, including herbarium specimens, paleontological museum specimens, and iNaturalist observations. We demonstrate the utility of the PteridoPortal through discussion of three example PteridoPortal‐enabled research projects. ResultsThe data within the PteridoPortal are global in scope and are queryable in a flexible manner. The PteridoPortal contains a taxonomic thesaurus (a digital version of a Linnaean classification) that includes both extant and extinct pteridophytes in a common phylogenetic framework. The PteridoPortal allows applications such as greatly accelerated classic floristics, entirely new “next‐generation” floristic approaches, and the study of environmentally mediated evolution of functional morphology across deep time. DiscussionThe PCC and PteridoPortal provide a comprehensive resource enabling novel research into plant evolution, ecology, and conservation across deep time, facilitating rapid floristic analyses and other biodiversity‐related investigations, and providing new opportunities for education and community engagement. 

This paper proposes an online gain adaptation approach to enhance the robustness of whole-body control (WBC) framework for legged robots under unknown external force disturbances. Without properly accounting for external forces, the closed-loop control system incorporating WBC may become unstable, and therefore the desired task goals may not be achievable. To study the effects of external disturbances, we analyze the behavior of our current WBC framework via the use of both full-body and centroidal dynamics. In turn, we propose a way to adapt feedback gains for stabilizing the controlled system automatically. Based on model approximations and stability theory, we propose three conditions to ensure that the adjusted gains are suitable for stabilizing a robot under WBC. The proposed approach has four contributions. We make it possible to estimate the unknown disturbances without force/torque sensors. We then compute adaptive gains based on theoretic stability analysis incorporating the unknown forces at the joint actuation level. We demonstrate that the proposed method reduces task tracking errors under the effect of external forces on the robot. In addition, the proposed method is easy-to-use without further modifications of the controllers and task specifications. The resulting gain adaptation process is able to run in real-time. Finally, we verify the effectiveness of our method both in simulations and experiments using the bipedal robot Draco2 and the humanoid robot Valkyrie . 

This paper proposes a method to generate feasible trajectories for robotic systems with predefined sequences of switched contacts. The proposed trajectory generation method relies on sampling-based methods, optimal control, and reach-ability analysis. In particular, the proposed method is able to quickly test whether a simplified model-based planner, such as the Time-to-Velocity-Reversal planner, provides a reachable contact location based on reachability analysis of the multi-body robot system. When the contact location is reachable, we generate a feasible trajectory to change the contact mode of the robotic system smoothly. To perform reachability analysis efficiently, we devise a method to compute forward and backward reachable sets based on element-wise optimization over a finite time horizon. Then, we compute robot trajectories by employing optimal control. The main contributions of this study are the following. Firstly, we guarantee whether planned contact locations via simplified models are feasible by the robot system. Secondly, we generate optimal trajectories subject to various constraints given a feasible contact sequence. Lastly, we improve the efficiency of computing reachable sets for a class of constrained nonlinear systems by incorporating bi-directional propagation (forward and backward). To validate our methods we perform numerical simulations applied to a humanoid robot walking.