An Amphibious Fully-Soft Miniature Crawling Robot Powered by Electrohydraulic Fluid Kinetic Energy

Miniature locomotion robots with the ability to navigate confined environments show great promise for a wide range of tasks, including search and rescue operations. Soft miniature locomotion robots, as a burgeoning field, have attracted significant research interest due to their exceptional terrain adaptability and safety features. In this paper, we introduce a fully-soft miniature crawling robot directly powered by fluid kinetic energy generated by an electrohydraulic actuator. Through optimization of the operating voltage and design parameters, the crawling velocity of the robot is dramatically enhanced, reaching 16 mm/s. The optimized robot weighs 6.3 g and measures 5 cm in length, 5 cm in width, and 6 mm in height. By combining two robots in parallel, the robot can achieve a turning rate of approximately 3 degrees/s. Additionally, by reconfiguring the distribution of electrodes in the electrohydraulic actuator, the robot can achieve 2 degrees-of-freedom translational motion, improving its maneuverability in narrow spaces. Finally, we demonstrate the use of a soft water-proof skin for underwater locomotion and actuation. In comparison with other soft miniature crawling robots, our robot with full softness can achieve relatively high crawling velocity as well as increased robustness and recovery

Sora Generates Videos with Stunning Geometrical Consistency

The recently developed Sora model [1] has exhibited remarkable capabilities in video generation, sparking intense discussions regarding its ability to simulate real-world phenomena. Despite its growing popularity, there is a lack of established metrics to evaluate its fidelity to real-world physics quantitatively. In this paper, we introduce a new benchmark that assesses the quality of the generated videos based on their adherence to real-world physics principles. We employ a method that transforms the generated videos into 3D models, leveraging the premise that the accuracy of 3D reconstruction is heavily contingent on the video quality. From the perspective of 3D reconstruction, we use the fidelity of the geometric constraints satisfied by the constructed 3D models as a proxy to gauge the extent to which the generated videos conform to real-world physics rules. Project page: https://sora-geometrical-consistency.github.io/Comment: 5 pages, 3 figure

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning

Graph Neural Networks (GNNs) have emerged as the de facto standard for representation learning on graphs, owing to their ability to effectively integrate graph topology and node attributes. However, the inherent suboptimal nature of node connections, resulting from the complex and contingent formation process of graphs, presents significant challenges in modeling them effectively. To tackle this issue, Graph Structure Learning (GSL), a family of data-centric learning approaches, has garnered substantial attention in recent years. The core concept behind GSL is to jointly optimize the graph structure and the corresponding GNN models. Despite the proposal of numerous GSL methods, the progress in this field remains unclear due to inconsistent experimental protocols, including variations in datasets, data processing techniques, and splitting strategies. In this paper, we introduce OpenGSL, the first comprehensive benchmark for GSL, aimed at addressing this gap. OpenGSL enables a fair comparison among state-of-the-art GSL methods by evaluating them across various popular datasets using uniform data processing and splitting strategies. Through extensive experiments, we observe that existing GSL methods do not consistently outperform vanilla GNN counterparts. However, we do observe that the learned graph structure demonstrates a strong generalization ability across different GNN backbones, despite its high computational and space requirements. We hope that our open-sourced library will facilitate rapid and equitable evaluation and inspire further innovative research in the field of GSL. The code of the benchmark can be found in https://github.com/OpenGSL/OpenGSL.Comment: 9 pages, 4 figure

Motion Kinematics Analysis of a Horse Inspired Terrain-Adaptive Unmanned Vehicle With Four Hydraulic Swing Arms

All terrain vehicles (ATV) perform tasks in unstructured environments where the advanced adaptive ability of rigid terrain has become a key factor. In this article, we propose a novel horse inspired all terrain eight-wheeled vehicle with four swing arms for transportation in the mountain battlefield. The mechanism structure and system configuration of the ATV are designed based on the horse leg kinematics analysis. In order to analyze the obstacle surmounting strategy of the ATV, the kinematics model and the center of gravity of the ATV are represented. A model reference adaptive control method is proposed for the hydraulic attitude control system. Then the model for obstacle surmounting is proposed for dynamics performance and geometric kinematics. Additionally, the simulation is executed in Adams to verify the analysis and strategy. Finally, the experiment is demonstrated for climbing a vertical wall, which is a challenging and typical terrain of the mountain battlefield

A Muscle Teleoperation System of a Robotic Rollator Based on Bilateral Shared Control

The approach that achieves the teleoperation between human muscle signals and the mobile robot is increasingly applied to transfer human muscle stiffness to enhance robotic performance. In this paper, we develop a mobile rollator control system applying a muscle teleoperation interface and a shared control method to enhance the obstacle avoidance in an effective way. In order to control intuitively, haptic feedback is utilized in the teleoperation interface and is integrated with EMG stiffness to provide a large composition force. Then the composition force is implemented with an artificial potential field method to keep the robotic rollator away from the obstacle in advance. This algorithm is superior to the traditional APF algorithm regardless of the required time and trajectory length. The experimental results demonstrate the effectiveness of the proposed muscle teleoperation system

Common dc-link capacitor harmonic current minimization for cascaded converters by optimized phase-shift modulation

This paper investigates the influence of a constant carrier phase shift on the DC-link capacitor harmonic current of cascaded converters used in fuel-cell and mild-hybrid electric vehicles. In these applications, a DC-DC converter can be adopted between the battery and the motor drive inverter in a cascaded structure, where the two converters share the same DC-link. Since the DClink capacitor of such a system represents a critical component, the optimization of the converter operation to limit the current stress and extend the lifetime of the capacitor is an primary objective. This paper proposes the use of a carrier phase shift between the modulations of the two converters in order to minimize the harmonic current of the DC-link capacitor. By harmonic analysis, an optimal carrier phase shift can be derived depending on the converter configuration. Analytical results are presented and validated by hardware-in-the-loop experiments. The findings show that the pulse width modulation carrier phase shift between the interleaved boost converter and the voltage source motor drive inverter has a significant influence on the DC-link capacitor current and thus on its lifetime. A case study with two-cell and three-cell interleaved boost converters shows a possible DC-link capacitor lifetime extension of up to 390%.peer-reviewe

Application of Angiotensin Receptor–Neprilysin Inhibitor in Chronic Kidney Disease Patients: Chinese Expert Consensus

Chronic kidney disease (CKD) is a global public health problem, and cardiovascular disease is the most common cause of death in patients with CKD. The incidence and prevalence of cardiovascular events during the early stages of CKD increases significantly with a decline in renal function. More than 50% of dialysis patients die from cardiovascular disease, including coronary heart disease, heart failure, arrhythmia, and sudden cardiac death. Therefore, developing effective methods to control risk factors and improve prognosis is the primary focus during the diagnosis and treatment of CKD. For example, the SPRINT study demonstrated that CKD drugs are effective in reducing cardiovascular and cerebrovascular events by controlling blood pressure. Uncontrolled blood pressure not only increases the risk of these events but also accelerates the progression of CKD. A co-crystal complex of sacubitril, which is a neprilysin inhibitor, and valsartan, which is an angiotensin receptor blockade, has the potential to be widely used against CKD. Sacubitril inhibits neprilysin, which further reduces the degradation of natriuretic peptides and enhances the beneficial effects of the natriuretic peptide system. In contrast, valsartan alone can block the angiotensin II-1 (AT1) receptor and therefore inhibit the renin–angiotensin–aldosterone system. These two components can act synergistically to relax blood vessels, prevent and reverse cardiovascular remodeling, and promote natriuresis. Recent studies have repeatedly confirmed that the first and so far the only angiotensin receptor–neprilysin inhibitor (ARNI) sacubitril/valsartan can reduce blood pressure more effectively than renin–angiotensin system inhibitors and improve the prognosis of heart failure in patients with CKD. Here, we propose clinical recommendations based on an expert consensus to guide ARNI-based therapeutics and reduce the occurrence of cardiovascular events in patients with CKD