Closed-loop Path Research Articles

An Indoor 3D Positioning Method Using Terrain Feature Matching for PDR Error Calibration

Pedestrian Dead Reckoning (PDR) is a promising algorithm for indoor positioning. However, the accuracy of PDR degrades due to the accumulated error, especially in multi-floor buildings. This paper introduces a three-dimensional (3D) positioning method based on terrain feature matching to reduce the influence of accumulated errors in multi-floor scenes. The proposed calibration method involves two steps: motion pattern recognition and position matching-based calibration. The motion pattern recognition aims to detect different motion patterns, i.e., taking the stairs or horizontal walking, from the streaming data. Then, stair entrances and corridor corners are matched with transition points of motion patterns and pedestrian turning points, respectively. After matching, calibration is performed to eliminate the accumulated errors. By carrying out experiments on a two-floor closed-loop path with a walking distance about 145 m, it is shown that this method can effectively reduce the accumulated error of PDR, achieving accurate 3D positioning. The average error is reduced from 6.60 m to 1.37 m.

New process allows full recovery of starting materials from tough polymer composites

On February 8, 2024, the Oak Ridge National Laboratory, announced, that inventors at the Department of Energy's Oak Ridge National Laboratory have designed a closed-loop path for synthesizing an exceptionally tough carbon-fiber-reinforced polymer, or CFRP, and later recovering all of its starting materials.

Risk spillovers in Chinese production network: A supply-side shock perspective

Highly interconnected production network exists in one economy, and it is crucial to investigate how and why supply-side shocks spread across industries via the production network and cause systemic risks in the real sector. Based on input-output framework, this paper designed a model to simulate the propagation of risk spillovers along the production network given supply-side shocks. This paper defined the systemically important industries (SIIs) and systemically vulnerable industries (SVIs) according to the degree and direction of risk spillovers. Simulation results show that risk spillovers spread among industries via the production network, leading to systemic risk in the real sector. This paper also classified the important risk spillover paths “SVIs → SIIs → SVIs” in the model for risk regulation and prevention and identified 75 risk spillover paths and 9 closed-loop paths in 2018. Furthermore, key factors of systemic importance (vulnerability) included input-output relationships and production network centrality. This paper provides a scientific basis to strengthen the risk supervision of the real sector based on the supply chain.

Pathways to achieve low-carbon transition in the transportation sector under the constraints of carbon peak and carbon neutrality targets: A comprehensive analysis of intra- and extra-industry factors

Carbon emission mechanisms in the transportation sector are complex due to a linkage of intra- and extra-industry factors. The decomposition techniques of emission reduction factors are more inclined to analyze conventional factors and need to pay more attention to non-conventional factors. This paper proposes a new analysis framework and builds the LMDI@1 model based on the general analysis theory of index decomposition. In this direction, we calculate China's transportation carbon emissions (TCE) from 2005 to 2020 through direct and indirect sources. Within this model, extra-industry factors are linked into the system to analyze more clearly the degree of factors' contribution to TCE changes in China's regional perspective and clarify potential factors' interaction patterns. We find that factors' contribution has temporal and regional differences. Intra-industry and extra-industry factors form four closed-loop carbon reduction paths at economic development, resource allocation, industrial structure, and resource endowment levels. Therefore, the low-carbon transition policy of China's transportation sector should consider the interaction between external policies and the endogenous environment.

A Multi-Stage Real-Time Fast Search Method for Closed-Loop Paths Based on Grid Hierarchical Partitioning Characteristics

Prior to switching operations, the dispatch automation system is required to be able to search for closed-loop paths quickly in real time. In order to improve the efficiency of closed-loop path search, this paper proposes a multi-stage real-time fast search method for closed-loop paths based on the characteristics of power grid hierarchical partitioning. First, we divide the closed-loop judgement process into three phases: initialization, acceptance of the closed-loop judgement command, and post-operation. Then, we define three types of nodes, including root nodes, same-layer contact nodes, and common nodes, and construct path data models for each type of node in accordance with the node liaison relationship in grid hierarchical zoning. In the initialization phase, we design a method for the automatic generation of real-time nodal path data models and study a hierarchical partitioned closed-loop path search method based on a nodal path data model for the phase of accepting closed-loop judgement commands. Next, we design a fast local correction method for nodal path models after the switch closure and disconnection operations in the post-operation idle phase are performed. Finally, a real power grid model is used as an example to test the above closed-loop path search method, which improves the search efficiency by eight times compared with the conventional breadth-first search method. The method is applicable to real large and complex power grids.

4-Methyl-5-vinyl thiazole modified Ni-MOF/g-C3N4/CdS composites for efficient photocatalytic hydrogen evolution without precious metal cocatalysts

The construction of heterojunction systems is an effective way to efficiently generate hydrogen by water photolysis. In this work, Ni-MOF (trimesic acid, (BTC)) and g-C3N4 (denoted as CN) were combined, and then Ni-MOF/CN was modified by 4-Methyl-5-vinyl thiazole (denoted as MVTh). Finally, CdS was loaded on the surface of Ni-MOF/CN/MVTh to prepare the photocatalyst Ni-MOF/g-C3N4/MVTh/CdS (denoted as Ni/CN/M/Cd) with a triangular closed-loop path heterojunction for the first time. As a photocatalyst without precious metal cocatalysts, Ni/CN/M/Cd displayed high H2 evolution (17.844 mmol·g−1·h−1) under an optimum CdS loading of 40 wt%. The H2 evolution rate was approximately 79 times that of Ni-MOF/CN and exceeded those of almost all catalysts based on MOF/CN in the literature. The triangular closed-loop heterojunction formed between Ni-MOF, g-C3N4, and CdS could realize the directional migration of photocarriers and significantly diminished the transfer resistance of carriers. The Ni2+ in Ni-MOF provided many cocatalytic sites for H2 evolution via g-C3N4 and CdS. Furthermore, charge carrier separation in Ni-MOF/CN/CdS improved after the innovative addition of MVTh. This study provides a reference for the construction of a closed-loop heterojunction system without precious metal cocatalysts.

The Construction of a Closed Loop for Recycling from the Perspective of Industrial Ecology

This paper provides a systematic summary of the construction of urban recycling resources in China from an industrial ecology perspective. Firstly, it analyzes the development history and trends of urban recycling resources in China and compares traditional recycling resource treatment paths to highlight problems such as resource loss and irregular construction. Additionally, the paper proposes a closed-loop path for the utilization of China's urban recycling resources, which can serve as a reference for addressing current recycling resource challenges. This closed-loop path of recycling resource utilization, characterized by the principles of reduction, reuse, and resourcefulness, involves the participation of various stakeholders such as government, enterprises, and producers, and offers valuable suggestions to further enhance the development of urban recycling resources in China.

Improved Optimization Strategy Based on Region Division for Collaborative Multi-Agent Coverage Path Planning

In this paper, we investigate the algorithms for traversal exploration and path coverage of target regions using multiple agents, enabling the efficient deployment of a set of agents to cover a complex region. First, the original multi-agent path planning problem (mCPP) is transformed into several single-agent sub-problems, by dividing the target region into multiple balanced sub-regions, which reduces the explosive combinatorial complexity; subsequently, closed-loop paths are planned in each sub-region by the rapidly exploring random trees (RRT) algorithm to ensure continuous exploration and repeated visits to each node of the target region. On this basis, we also propose two improvements: for the corner case of narrow regions, the use of geodesic distance is proposed to replace the Eulerian distance in Voronoi partitioning, and the iterations for balanced partitioning can be reduced by more than one order of magnitude; the Dijkstra algorithm is introduced to assign a smaller weight to the path cost when the geodesic direction changes, which makes the region division more "cohesive", thus greatly reducing the number of turns in the path and making it more robust. The final optimization algorithm ensures the following characteristics: complete coverage of the target area, wide applicability of multiple area shapes, reasonable distribution of exploration tasks, minimum average waiting time, and sustainable exploration without any preparation phase.

Leakage Current Mitigation Technique in Solar PV Array System Using Passive Filter

The parasitic capacitances in the transformerless solar photovoltaic (PV) array system develop the closed-loop path and generate the leakage current. As a result, it hampers the system performance with the presence of the leakage current such as electromagnetic interference, lessened the lifespan of PV panel, etc. To solve these issues, the passive filter is designed herein for the solar PV array system to suppress the leakage current. The frequency-domain analysis of the system is performed herein to carry out the optimum filter parameters. In this design approach, there is not any need for additional semiconductor switches, unlike the state-of-art systems. The adaptive controller is adopted herein to extract the fundamental component of the load current in order to provide effective harmonic compensation. Simulation results demonstrate that the presented passive filter effectively suppresses the leakage current within limits based on the DIN and NB/T grid codes. Additionally, several comparative analyses are performed to validate the practical feasibility and effectiveness of the presented system. The real-time hardware-in-loop (HIL) performance is analyzed for manifold operating cases. The total harmonic distortions (THDs) of the grid currents are accomplished within 5% as per the revised IEEE standard 519 and IEC standard 61727.

Recommender system for ablation lines to treat complex atrial tachycardia

Background and Objective: Planning the optimal ablation strategy for the treatment of complex atrial tachycardia (CAT) is a time consuming task and is error-prone. Recently, directed network mapping, a technology based on graph theory, proved to efficiently identify CAT based solely on data of clinical interventions. Briefly, a directed network was used to model the atrial electrical propagation and reentrant activities were identified by looking for closed-loop paths in the network. In this study, we propose a recommender system, built as an optimization problem, able to suggest the optimal ablation strategy for the treatment of CAT.Methods: The optimization problem modeled the optimal ablation strategy as that one interrupting all reentrant mechanisms while minimizing the ablated atrial surface. The problem was designed on top of directed network mapping. Considering the exponential complexity of finding the optimal solution of the problem, we introduced a heuristic algorithm with polynomial complexity. The proposed algorithm was applied to the data of i) 6 simulated scenarios including both left and right atrial flutter; and ii) 10 subjects that underwent a clinical routine.Results: The recommender system suggested the optimal strategy in 4 out of 6 simulated scenarios. On clinical data, the recommended ablation lines were found satisfactory on 67% of the cases according to the clinician’s opinion, while they were correctly located in 89%. The algorithm made use of only data collected during mapping and was able to process them nearly real-time.Conclusions: The first recommender system for the identification of the optimal ablation lines for CAT, based solely on the data collected during the intervention, is presented. The study may open up interesting scenarios for the application of graph theory for the treatment of CAT.

Closed-loop controlled conformal 3D printing on moving objects via tool-localized object position sensing

The ability to functionalize and inspect moving objects is central to various emerging additive manufacturing (AM) applications, including in situ bioprinting and 3D printing in extreme conditions (e.g., space). This work provides a novel closed-loop controlled path planning method for planar and nonplanar microextrusion 3D printing on moving substrates and objects via real-time sensing of local object-tool offset that requires no description of the object's global geometry. Feedback control of the microextrusion nozzle z-axis position via real-time sensing of nozzle-surface offset using 1D laser displacement sensors enabled conformal 3D printing on moving substrates and objects. The method's utility was demonstrated by microextrusion 3D printing on planar substrates oscillating at the frequencies associated with tissue motion caused by human physiological processes, including respiration and the heartbeat. The method enabled conformal microextrusion 3D printing in the presence of substrate or object motion, including random vertical displacement (i.e., step changes) and continuous vibration (amplitude (A) = 0.8–6.7d, frequency (f) = 0.2, 0.4 and 1.3 Hz, where d is the nozzle diameter). The method was also validated by conformal microextrusion 3D printing on a human hand undergoing random vertical motion (A = 0–34.5d). This work advances closed-loop path planning for microextrusion 3D printing on moving substrates and objects. The created closed-loop path planning methodology and AM process may support various emerging AM applications, including in situ bioprinting and AM in mobile and extreme environments prone to mechanical disturbance, such as vehicles, vessels, aircraft, and spacecraft.

Effects of Closed-Loop Devices on Omnidirectional Beam Patterns Radiated from WAVE Monopole Antennas

This study investigates the influence of closed-loop devices on omnidirectional beam patterns radiated from a Wireless Access for Vehicle Environment (WAVE) monopole antenna for facilitating communication stability in Vehicle-to-Vehicle and Vehicle-to-Everything technology. Single, dual, and quadruple closed-loop devices were introduced into the monopole antenna, and their surface current density and radiation beam patterns were analyzed by using the high-frequency structure simulator (HFSS) and computer simulation technology (CST) programs. As the closed-loop devices reflected the signal radiated from the antenna, the distribution of the surface current was concentrated around the monopole due to the creation of a closed-loop surface current path, which increased the gain value. The average gain was considerably increased by introducing closed-loop devices. The proposed antenna has an average gain of 1.57 dBi and a peak gain of 6.29 dBi at the operating frequency. Furthermore, omnidirectional beam patterns with a beam width of 359° were obtained by introducing four closed-loop devices into the monopole antenna, which eliminated nearly all null points in the frequency range of 5.85–5.925 GHz.

Design of UVC Surface Disinfection Robot with Coverage Path Planning Using Map-Based Approach At-The-Edge

In response to the issue of virus contamination in the cold-chain warehouse or hospital environment under the influence of the COVID-19, we propose the design work of a disinfection robot based on the UVC radiation mechanism using the low-computational path optimization at-the-edge. To build a surface disinfection robot with less computing power to generate a collision-free path with shorter total distance in studies, a 2D map is used as a graph-based approach to automatically generate a closed-loop disinfection path to cover all the accessible surfaces. The discrete disinfection points from the map are extracted with effective disinfection distances and sorted by a nearest-neighbor (NN) search over historical trajectory data and improved A * algorithm to obtain an efficient coverage path to all accessible boundaries of the entire area. The purpose of improved A * algorithm with NN is not to find the optimal path solution but to optimize one with reasonable computing power. The proposed algorithm enhances the path-finding efficiency by a dynamically weighted heuristic function and reduces the path turning angles, which improves the path smoothness significantly requiring less computing power. The Gazebo simulation is conducted, and the prototype disinfection robot has been built and tested in a real lab environment. Compared with the classic A * algorithm, the improved A * algorithm with NN has improved the path-finding efficiency and reduced the path length while covering the same area. Both the simulation and experimental results show that this approach can provide the design to balance the tradeoffs among the path-finding efficiency, smoothness, disinfection coverage, and computation resources.

Evaluation of damping of subsynchronous interaction between direct-drive wind farm and LCC-HVDC based on the damping path analysis

The interaction between direct-drive wind farm (DDWF) and LCC-HVDC may make the power system more prone to subsynchronous oscillation (SSO). This paper presents a damping path analysis method to analyze and evaluate the subsynchronous interaction between them from the perspective of the internal disturbance transfer of the system. First, damping torque analysis (DTA) is extended to the SSO mode dominated by phase-locked loop (PLL), and the stability of the DDWF with the LCC-HVDC (DDWFL) system is analyzed. Then based on the closed-loop transfer function block diagram of the DDWFL system, the disturbance transfer process between DDWF and LCC-HVDC is revealed to analyze the interaction mechanism in the SSO mode, and the closed-loop disturbance transfer paths that reflect the system damping are called the damping paths. Further, damping path of the subsynchronous interaction between DDWF and LCC-HVDC is separated, and its effect on the SSO mode damping is evaluated by damping coefficient. It is concluded that the SSO mode dominated by PLL has instability risk in the DDWFL system, and the subsynchronous interaction between DDWF and LCC-HVDC provides negative damping to the system. Finally, the time domain simulation results demonstrate the validation of damping evaluation based on damping path analysis.

A Resonant Ring Topology Approach to Power Line Communication Systems within Photovoltaic Plants

Within this study, single-cable propagation facilitated by PV strings’ wiring characteristics is considered for an adapted design of PLC electronics. We propose to close the communications signal path, resulting in a ring topology where a resonance condition could be implemented. A PLC topology using the resulting circular closed-loop path of a PV series string as its physical communication support is designed and leveraged for practical use. When the path length or the number of transceivers is changed, the resonance properties that come with the circular path as the physical support are affected but are shown to be preserved with the application of automatic adjustable tuning. This automatic tuning guarantees that the resonance improves propagation parameters and reverts the system to its optimal values at the chosen carrier frequency.

Keeping an Eye on Things: Deep Learned Features for Long-Term Visual Localization

In this letter, we learn visual features that we use to first build a map and then localize a robot driving autonomously across a full day of lighting change, including in the dark. We train a neural network to predict sparse keypoints with associated descriptors and scores that can be used together with a classical pose estimator for localization. Our training pipeline includes a differentiable pose estimator such that training can be supervised with ground truth poses from data collected earlier, in our case from 2016 and 2017 gathered with multi-experience Visual Teach and Repeat (VT&R). We insert the learned features into the existing VT&R pipeline to perform closed-loop path following in unstructured outdoor environments. We show successful path following across all lighting conditions despite the robot’s map being constructed using daylight conditions. Moreover, we explore generalizability of the features by driving the robot across all lighting conditions in new areas not present in the feature training dataset. In all, we validated our approach with 35.5 km of autonomous path following experiments in challenging conditions.

Earth energy evolution, human development and carbon neutral strategy

Energy is the basis of human development and the impetus of society progress. There are three sources of energy: energy of celestial body outside the Earth, the Earth energy and energy of interaction between the Earth and other celestial bodies. Meanwhile, there are three scales of co-evolution: the evolution of the Sun-Earth-Moon system on an ultra-long time scale has provided energy sources and extra-terrestrial environmental conditions for the formation of the Earth system; the evolution of the Earth system on a long time scale has provided the material preconditions such as energy resources and suitable sphere environment for life birth and the human development; on a short time scale, the development of human civilization makes the human circle break through the Earth system, expanding the extraterrestrial civilization. With the co-evolution, there are three processes in the carbon cycle: inorganic carbon cycle, short-term organic carbon cycle and long-term organic carbon cycle, which records human immoderate utilization of fossil energy and global sphere reforming activities, breaking the natural balance and closed-loop path of the carbon cycle of the Earth, causing the increase of greenhouse gases and global climate change, affecting human happiness and development. The energy transition is inevitable, and carbon neutrality must be realized. Building the green energy community is a fundamental measure to create the new energy system under carbon neutrality target. China is speeding up its energy revolution and developing a powerful energy nation. It is necessary to secure the cornerstone of the supply of fossil energy and forge a strong growing pole for green and sustainable development of new energy. China energy production and consumption structure will make a revolutionary transformation from the type of fossil energy domination to the type of new energy domination, depending on a high-level self-reliance of science and technology and a high-quality green energy system of cleaning, low-carbon, safety, efficiency and independence. Energy development has three major trends: low-carbon fossil energy, large-scale new energy and intelligent energy system, relying on the green innovation, contributing the green energy and constructing the green homeland.

Optimal Path Planning for Wireless Power Transfer Robot Using Area Division Deep Reinforcement Learning

This paper aims to solve the optimization problems in far-field wireless power transfer systems using deep reinforcement learning techniques. The Radio-Frequency (RF) wireless transmitter is mounted on a mobile robot, which patrols near the harvested energy-enabled Internet of Things (IoT) devices. The wireless transmitter intends to continuously cruise on the designated path in order to fairly charge all the stationary IoT devices in the shortest time. The Deep Q-Network (DQN) algorithm is applied to determine the optimal path for the robot to cruise on. When the number of IoT devices increases, the traditional DQN cannot converge to a closed-loop path or achieve the maximum reward. In order to solve these problems, an area division Deep Q-Network (AD-DQN) is invented. The algorithm can intelligently divide the complete charging field into several areas. In each area, the DQN algorithm is utilized to calculate the optimal path. After that, the segmented paths are combined to create a closed-loop path for the robot to cruise on, which can enable the robot to continuously charge all the IoT devices in the shortest time. The numerical results prove the superiority of the AD-DQN in optimizing the proposed wireless power transfer system.

Resilient Consensus in Robot Swarms With Periodic Motion and Intermittent Communication

In this article, we propose an approach to construct a time-varying communication topology with a resilient consensus performance for robot swarms with limited communication ranges. The robots are deployed to explore a large task space and achieve consensus despite the existence of a finite number of noncooperative members in the team. Existing methods encouraged robots to stay close to each other to achieve certain robustness requirements on the connectivity of the communication topology. We leverage on the robots’ mobility to design a time-varying integrated topology composed of several subgroups of robots deployed on nonoverlapping closed-loop paths. Robots are spread out and move along the paths, forming periodic communication links within or across groups. We analyze the time-varying topology synthesized and provide sufficient conditions for individual subgroups and the interconnection between them. We show designs satisfying the conditions with simulated examples in a lattice space, as well as in a task space with predefined paths.

Pigeon-inspired optimisation-based cooperative target searching for multi-UAV in uncertain environment

In this paper, the multi-UAV cooperative target searching problem is investigated and a close loop path planning method is developed for UAVs in uncertain environment. The proposed method includes two consecutive parts, the multi-UAV cooperative target search algorithm developed based on cooperative pigeon-inspired optimisation (CPIO) and the base returning algorithm for each UAV based on artificial potential field (APF) method. Firstly, a concerned regional environment and the initial search probability map models are established. Then, by applying the rolling prediction strategy, the cooperative target search paths for multiple UAVs are generated by utilising the proposed CPIO. With this method, UAVs can reinforce target search in the key areas in a cooperative way and avoid flying into the no-fly zones. In the meanwhile, the Bayesian theorem is used to constantly update the search probability map in each search step. Finally, at the end of the target search phase, an optimised safe path is generated for each UAV returning back to its original by using the APF method. Simulations are performed and the results demonstrate that the proposed approach is effective for multiple UAVs carrying out cooperative target search task in a complex environment.