Redundant Paths Research Articles

A Novel Exploration Mechanism of RRT Guided by Deep Q-Network

A novel exploration mechanism for addressing the issues of slow convergence speed, excessive redundancy and low path quality associated with the inherent randomness of Rapidly-exploring Random Tree (RRT)’s sampling approach is presented. First, the node exploration process of the RRT algorithm is modeled as a Markov Decision Process (MDP) by designing the action space and reward function. Subsequently, a novel node exploration mechanism based on RRT-Connect is developed by integrating environmental feedback information. Finally, the combination of Deep Q-Network (DQN) and RRT is achieved through the proposed DQN-RRT algorithm, which incorporates the structure and training method of DQN. Compared to the traditional RRT algorithm, the proposed algorithm balances planning autonomy, reduces search redundancy and efficient obstacle avoidance. Simulations are given to validate the performance optimization function of the proposed algorithm in RRT path planning.

Exploration-based model learning with self-attention for risk-sensitive robot control

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics that involve inherent randomness, which may cause instability or malfunction of the target system and render the system susceptible to external perturbations. In this paper, we propose an online model update algorithm that can be directly operated in real-world robot systems. The algorithm leverages a self-attention mechanism embedded in neural networks for the kinematics and the dynamics models of the target system. The approximated model involves redundant self-attention paths to the time-independent kinematics and dynamics models, allowing us to detect abnormalities by calculating the trace values of the self-attention matrices. This approach reduces the randomness during the exploration process and enables the detection and rejection of detected perturbations while updating the model. We validate the proposed method in simulation and with real-world robot systems in three application scenarios: path tracking of a soft robotic manipulator, kinesthetic teaching and behavior cloning of an industrial robotic arm, and gait generation of a legged robot. All of these demonstrations are achieved without the aid of simulation or prior knowledge of the models, which supports the proposed method’s universality for various robotics applications.

DRL-based routing algorithm with guaranteed loss, latency and bandwidth in SDN networks: Application of online video conferencing

Technology development in traffic engineering has led to the re-architecting of Online Video Conferencing Services (OVCS) through Software-Defined Networking (SDN) to provide scalability and low-latency performance. Since OVCS requires significant network bandwidth, routing algorithms must consider issues such as path redundancy, network congestion, and the rate of requested resources. With this motivation, this paper proposes a routing algorithm based on Deep Reinforcement Learning (DRL) to handle online video conference connection requests in SDN, which can simultaneously guarantee packet loss, latency, and bandwidth. The learning agent is configured based on the Asynchronous Advantage Actor-Critic (A3C) algorithm, which can adapt to the current traffic conditions and reduce the service latency as much as possible. We adjust the weights of the links in the weighted shortest path algorithm based on a set of critical nodes to improve the convergence ability of A3C and reduce the dependence of the learning agent on the network topology. Here, the link weight is measured by considering the critical nodes under maximum flow and minimum latency, configured to reduce interference in future routings. In addition, a postponement strategy is embedded in the SDN controller to prioritize requests based on the resources demanded for routing. This strategy is activated during network congestion and provides the ability to reserve more resources for future requests. The experimental results show that the proposed algorithm has a promising performance and convergence compared to the existing solutions and guarantees the QoS of OVCS. Specifically, the proposed algorithm can improve the throughput (up to 2.8%) and admission rate (up to 1.8%) of OVCS connection compared to the best existing solution.

RESEARCH AND DESIGN OF A PATH PLANNING USING AN IMPROVED RRT* ALGORITHM FOR AN AUTONOMOUS MOBILE ROBOT

Path planning is innately viewed as a multi-objective optimization problem (MOOP) of the shortest path and the smallest distance to collision-free obstacles. The position of the mobile robot is definitively identified based on data derived from constructing maps with SLAM or extracting data from camera frames. Due to the complexity of the surroundings, obstacle avoidance still requires a complex sensor system with a high processing efficiency demand. The study provides an improved RRT* algorithm for mobile robot path planning in a given environment. RRT* will optimize the number of grid nodes based on the optimal cost functions of nodes in the searching environment. The improved RRT* algorithm with a safety cost increases the efficacy of obstacle avoidance. Hence, an improved RRT* algorithm based on the traditional RRT algorithm will remove redundant path nodes. Furthermore, the third-degree B-spline curve will smooth the path while ensuring MOOPs. Last but not least, simulations and experiments are shown to demonstrate the effectiveness of the suggested strategy.

Active Thermal Control in Neutral-Point-Clamped Multilevel Converters Based on Switching-Cell Arrays

Neutral-point-clamped multilevel converters are a suitable solution to the implementation of low–medium voltage and power applications at present, thanks to their intrinsic superior voltage and current quality. The conventional configurations of these converters present uneven power loss distribution, causing thermal stress in some power semiconductors, which weakens the power converter reliability. To overcome this, an implementation of the neutral-point-clamped multilevel converter based on a switching-cell array is introduced, adding redundant conduction paths on one side and more options to distribute the switching losses on the other side. An active thermal control is proposed to balance the temperature distribution in the converter. A four-level converter has been implemented to evaluate the proposed solution. The experimental results show that the proposed implementation and active thermal control presents an enhanced temperature distribution in the converter and, therefore, reduced thermal stress and better reliability.

DETECTING ANOMALIES IN STRUCTURAL RESPONSE OF CABLE SUPPORTED BRIDGES: AFTER EXTREME EVENTS

AbstractThe safety of cable‐supported bridges primarily depends on cable design, proper tensioning during construction, and regular maintenance. Over the past decade, numerous cable‐supported bridges have faced various issues, including aging, poor tensioning practices, coping with heavy traffic loads, insufficient maintenance, and exposure to accidents or extreme conditions. Despite these challenges, these structures often withstand such problems due to the inclusion of redundancy and alternative load paths in their design. Detecting anomalies in bridge monitoring data can aid in identifying potential issues. Typically, only specific cables are monitored in a cable‐supported bridge monitoring system. The conditions of non‐monitored cables are usually estimated based on the data from adjacent cable sensors. The structural response of the tower and the deck can also be indirectly estimated. This research aims to present a methodology for detecting anomalies in structural responses following extreme events. It is crucial to differentiate temporary changes in cable measurements caused by expected seasonal temperature fluctuations, regular winds, and normal traffic patterns from permanent changes resulting from extreme events. Additionally, one must consider that a permanent change in measurements might also occur due to sensor loss after an extreme event. The paper will discuss tools to form a detection that can identify whether the source of change is due to a real extreme event or not.

3D smooth path planning of AUV based on improved ant colony optimization considering heading switching pressure

A smooth and secure spatial path planning algorithm that integrates the improved ant colony optimization with the corrective connected spatial search strategy is proposed, aiming at heavy heading switching pressure of autonomous underwater vehicles sailing in complex marine environment. On the one hand, to overcome the low-dimensional search domain and inaccurate spatial communication information in traditional spatial path planning, the spatial connectivity adjacency domain search strategy is designed based on grid environment model. On the other hand, to alleviate heading switching pressure due to large path steering angles and redundant path turning points, the heuristic functions and pheromone update criterion based on ant colony optimization are introduced to improve the solution quality of smooth paths. The simulation results show that the space search strategy can improve the success probability of safe path planning without reducing the scope of explorable free space. Additionally, the simulations demonstrate that the improved ant colony optimization using the spatial search strategy can guarantee the shortest path with lowest tortuous degree and fewest turning times in the same grid environment.

Navigation of Apple Tree Pruning Robot Based on Improved RRT-Connect Algorithm

Pruning branches of apple trees is a labor-intensive task. Pruning robots can save manpower and reduce costs. A full map of the apple orchard with collision-free paths, which is navigation planning, is essential. To improve the navigation efficiency of the apple tree pruning robot, an improved RRT-Connect algorithm was proposed. Firstly, to address the disadvantage of randomness in the expansion of the RRT-Connect algorithm, a goal-biased strategy was introduced. Secondly, to shorten the path length, the mechanism of the nearest node selection was optimized. Finally, the path was optimized where path redundancy nodes were removed, and Bezier curves were used to deal with path sharp nodes to further reduce the path length and improve the path smoothness. The experimental results of apple orchard navigation show that the improved algorithm proposed in this paper can cover the whole apple orchard, and the path length is 32% shorter than that of the RRT-Connect algorithm. The overall navigation time is 35% shorter than that of the RRT-Connect algorithm. This shows that the improved algorithm has better adaptability and planning efficiency in the apple orchard environment. This will contribute to the automation of orchard operations and provide valuable references for future research on orchard path planning.

Bi-objective optimization of last-train timetabling with multimodal coordination in urban transportation

When urban rail transit (URT) does not provide 24-hour services, passengers who travel at late night may not be able to reach their destinations with only URT trains. As a result, passengers have to find alternative transport means, or combine URT trains with other transport services to fulfill their journeys. This paper investigates the integrated optimization of last train timetabling and bridging service design with consideration of passenger path choices. Two bridging services are considered: taxis and buses. Based on pre-constructed path sets, a bi-objective mixed-integer nonlinear programming (MINLP) model is developed, aiming at minimizing total passenger travel time and total passenger travel cost. To reduce the model scale and improve solution efficiency, three path dominance principles are proposed to remove redundant passenger paths without loss of optimality. An adaptive iterative algorithm is designed to obtain the Pareto frontier curve. The proposed model and solution methods are demonstrated on the Chengdu URT network. Results indicate that passenger travel costs and travel times can be significantly reduced by the integrated optimization. It also provides passengers with a safer night travel environment due to the reduction in passenger travel times in taxis.

Ultrasonic inspection during autoclave cure of reflowable-interface composite joints

In structural bonds, the interface between adherend and adhesive is nearly two-dimensional making the interface susceptible to minute quantities of contamination, which can cause weak bonds. Regulatory organizations such as the Federal Aviation Administration (FAA) often require redundant load paths in secondary-bonded primary-structures due to uncertainty in bond performance. To address this issue, the NASA Convergent Aeronautics Solutions (CAS): Adhesive Free Bonding of Composites (AERoBOND) project is investigating reformulated aerospace epoxy-matrix resins to enable reflow and diffusion of the resin at the joint interface during a secondary bonding and cure process that can eliminate the material discontinuity at the interface. Implementing in-situ process monitoring enables assessing the bond quality during processing rather than waiting for post-fabrication mechanical testing to be completed. In this paper, an in-situ ultrasonic inspection system is used to monitor the joining of three composite laminates assembled using the AERoBOND technique. For each panel, the amplitude of the wave reflection at the joint was measured throughout the cure cycle. The results indicate the timing and extent of reflow and cure of the epoxy resin at the joint. Factors indicating end of cure were ascertained and a metric was developed to qualitatively predict acceptable mode-II fracture toughness based on the ultrasonic amplitude at the joint line during cure. In addition, since the inspection system scans an area of the joint, high-resolution localized results can be obtained across the joint.

Quantifying a virtual water metabolic network of the Metropolitan District of Quito, Ecuador using ecological network methods

AbstractCurrent human population is mostly located in urban areas making cities the center of attention in terms of achieving sustainability goals. Evidence shows that ecosystems have evolved over time toward a balanced configuration between resource efficiency and functional redundancy. For this reason, they are exemplary models to follow in terms of sustainability. Here, we apply similar ecological network‐based methods to study the virtual water metabolic network (VWMN) of the Metropolitan District of Quito. The VWMN was obtained using novel bottom‐up, survey‐based methods to generate the urban metabolic network. We compare the VWMN results with those previously obtained from ecological food webs, to learn if there are insights about the sustainability of urban metabolic processes. We conclude that VWMN does not exhibit characteristics observed in sustainable ecological networks because this socioeconomic network exhibits higher levels of path redundancy. Urban metabolism studies are gaining in popularity as a research tool aimed at informing resource management and this is one of the first covering a city in the Global South and using a bottom‐up survey method.

A Novel Modulation Strategy for Split-Inductor Active NPC Inverter With Loss Distribution Balancing and Thermal Stress Reduction

Neutral point clamped inverter (NPC) features low harmonics, high efficiency, and low voltage stress, et al. NPC is widely applied in renewable energy power generation systems, such as wind turbine power and photovoltaic. However, due to unbalanced power losses, NPC suffers inherent thermal unbalance among inner and outer power switches. A split-inductor active neutral point clamped inverter (SI-ANPC) was initially proposed to improve the operating reliability, providing the structural basis for balanced loss distributions. With this purpose, a novel modulation strategy with balanced loss distribution for SI-ANPC is proposed in this paper. The modulation strategy is analyzed under the unity and non-unity power factors. In specially, two redundant zero-state paths are fully used. Under the unity power factor, the power switches operate at the switching frequency or maintain the conduction state complementarily. Considering the phase angle in the non-unity power factor situation, the working patterns of power switches are rearranged to reduce the loss difference. The thermal stress is decreased on both occasions. Finally, loss calculation results, experimental waveforms, and thermal images of the inner and outer switches are presented to confirm the effectiveness of the proposed modulation strategy.

Robot path planning by integrating improved A* algorithm and DWA algorithm

Traversing many nodes, low search efficiency, path slanting through obstacles, many path redundancy points, and the inability of dynamic real-time obstacle avoidance are all typical problems of A* algorithm. In this paper, A robot path planning method combining improved A* algorithm and DWA algorithm is proposed.The ratio of the distance between the current point and the starting point and the target point is introduced into the heuristic function, and the search efficiency is improved through the optimized heuristic function; the neighborhood search principle is simplified to 5-neighborhood search, and the nodes adjacent to obstacles are deleted to reduce the traversal nodes while avoiding diagonal penetration of obstacles; redundant node improvement method is used to reduce the degree of path transition; finally the path key points of the improved A* algorithm are extracted and DWA algorithm is fused to realize the robot to avoid unknown obstacles. Finally, experiments are carried out on Matlab to prove the feasibility of the new algorithm.

Identifying influential nodes by leveraging redundant ties

Structure-based influential nodes identification is a long-term challenge in the study of complex networks. While global centrality-based approaches are generally considered to be more accurate and reliable, the requirements of complete network information and high computational complexity are hard to meet, limiting their applications in many practical scenarios. In addition, recent studies have highlighted the effect of cyclic structures introducing redundant paths in network connectivity and exaggerating the importance of traditional centrality measures. In this work, we develop a new centrality metric, called Multi-Spanning Tree-based Degree Centrality (MSTDC), to quantify node importance with linear complexity by leveraging redundant ties. MSTDC is calculated using the aggregation of degrees of a small number of spanning trees constructed with a few randomly selected root nodes. Experiments on synthetic and empirical networks reveal that MSTDC obtains superior performance than other benchmark network centralities in identifying influential nodes from the perspective of both maintaining network connectivity and maximizing spreading capacity. In addition, we find that MSTDC is extraordinarily effective in networks with high clustering coefficients. Our study provides novel insights into the role of redundant ties in network structural and functional analyses.

Investigations on MBSE modelling and dynamic performance assessment of an electrical trimmable horizontal stabilizer actuator

With the development of power-by-wire technology for more electric aircraft, the electro-mechanical actuator (EMA) has the advantages to replace the conventional hydraulic servo actuator in some aerospace flight controls. Conventional hydraulically powered trimmable horizontal stabilizer actuation (THSA) system is nowadays developed to be electrically supplied. Given their safety-criticality, no-back mechanism and redundant load paths are utilized to meet the flight control requirements. However, rare literatures have introduced these functions and addressed the virtual prototyping activities from system-level point of view. This paper proposed such a model of a THSA system with dual electric power sources and fault-tolerant mechanical load paths. The nonlinear effects of components are considered with realism, and system-level simulation test is conducted to support the model-based system engineering (MBSE) approach. The models are developed with a power view instead of a pure signal view. Focusing on the friction effect and compliance effect with backlash or preload, some improved and novel approaches are adopted for these crucial components and validated via experimental results. Meanwhile, the implemented system-level model enables injection of crucial faults. Finally, the simulation of the proposed model shows that it is an efficient resource to investigate the actuator’s dynamic performance, to virtually prove that the actuator meets the fail/safe constraint, and to demonstrate the soundness of the fault monitoring functions.

Improvement of Network Flow Using Multi-Commodity Flow Problem

In recent years, Internet traffic has increased due to its widespread use. This can be attributed to the growth of social games on smartphones and video distribution services with increasingly high image quality. In these situations, a routing mechanism is required to control congestion, but most existing routing protocols select a single optimal path. This causes the load to be concentrated on certain links, increasing the risk of congestion. In addition to the optimal path, the network has redundant paths leading to the destination node. In this study, we propose a multipath control with multi-commodity flow problem. Comparing the proposed method with OSPF, which is single-path control, and OSPF-ECMP, which is multipath control, we confirmed that the proposed method records higher packet arrival rates. This is expected to reduce congestion.

Plant Traits Variably Respond to Plant–Soil Interactions during Secondary Succession on the Loess Plateau

Knowledge of plant photosynthesis, biomass, and stress resistance could contribute to exploring the growth and restoration of vegetation. However, the response of these plant traits to plant–soil interactions at different successional stages remains poorly understood, which limits the understanding of secondary succession. A greenhouse experiment was designed to test the effects of rhizosphere soils collected from early- (EarlySoil), mid- (MidSoil), and late-successional (LateSoil) plant communities on plant traits of early-, mid-, and late-successional species (EarlySp, MidSp, and LateSp, respectively). We found that plant traits reacted in a specific direction to plant–soil interactions at different successional stages. Specifically, compared with treatments of plants growing in their own soil, the net photosynthetic rate and single-photon avalanche diode significantly increased in LateSp–EarlySoil (treatment of plants growing in soil) (20%–31%) and LateSp–MidSoil (10%–18%); the maximum quantum efficiency of photosystem II increased in MidSp–EarlySoil (1%) and LateSp–MidSoil (4%); belowground soluble sugar concentrations decreased in LateSp–EarlySoil (33%) and LateSp–MidSoil (45%); leaf, stem, and root biomass increased in MidSp–EarlySoil (76%–123%), LateSp–EarlySoil (180%–342%), and LateSp–MidSoil (83%–137%), and in turn they decreased in EarlySp–MidSoil (40%–73%) and EarlySp–LateSoil (53%–67%). The results indicated that soil conditioned by pre-successional species (early- or mid-successional species) would be conducive to plant functional traits of subsequent successional species (mid- or late-successional species). Constrained redundancy analysis and path analysis suggested that water-soluble ammonium N, total N, and available N concentrations were key soil factors affecting early-, mid-, and late-successional species, respectively. Our findings confirm the directionality of succession and provide new information for plant population dynamics during secondary succession.

Sub-Signal Channel Modulation for Hitless Redundancy Switching Systems

This paper proposes a sub-signal channel modulation scheme for hitless redundancy switching systems that offers highly confidential communications. A hitless redundancy switching system prevents frame loss by using multiple routes to forward the same frame. Although most studies on redundancy switching systems deal with frame duplication, elimination, and selection of redundant paths for the main signal, we focus on the transmission of the sub-signal channel. We introduce mathematical expressions to model the transmission rate and bit error rate of the sub-signal channel. To evaluate the validity of the models, we conduct numerical simulations to calculate the sub-signal transmission rate, main-signal transmission rate, and bit error rate of the sub-signal channel at physical transmission rates of 100Mb/s, 1Gb/s, and 10Gb/s. We discuss how to design sub-signal channel modulation on the basis of the evaluation results. We further discuss applications of sub-signal modulation in terms of network size and jitter.

Interlaminar mechanical performance of latent-cure epoxy joints

Because of uncertainty in bond strength of adhesively bonded composite structures for air flight, redundant load paths, such as mechanical fasteners or other crack arresting features, are required for certification. However, these redundant load paths add extra weight to the structure, induce significantly greater fabrication time and cost, and introduce local stress concentrations (in the case of mechanical fasteners) from which damage can more readily initiate. Structures with co-cured joints are more predictable, require much fewer redundant load paths, and are therefore more desirable. A secondary bonding technique for polymer-matrix composites that aims to produce co-cure-like joints with a continuous interface is briefly presented. A brief progression of mechanical testing results is reported and compared to actual co-cured joint performance. The purpose of the work is to determine the feasibility of this technology to produce a secondary bond equivalent in performance and predictability to that of a co-cured material. Joint performance was measured using six ASTM standard tests to measure interlaminar tensile and shear strength as well as mode-I and mode-II interlaminar fracture toughness at ambient temperature. After 50 process iterations, the final overall average joint performance exceeded 80% of the co-cured performance and in some tests had outperformed the co-cured specimens. The results suggest a high degree of feasibility of the technology to be pursued for future development with the intent to increase performance as well as reliability.

Performance-Based Retrofits of Long-Span Truss Bridges Based on the Alternate Load Path Redundancy Analysis

Existing long-span truss bridges typically undergo significant retrofits to improve their resistance against extreme load events, such as the seismic loads, for which the bridge may not have been designed or considered originally. However, the conventional seismic retrofit measures recommended in most existing codes and specifications may not be effective in providing sufficient alternative load path (ALP) redundancy to a bridge that is vulnerable to sudden member-loss scenarios because of the significantly different magnitude of demands. This paper proposed a performance-based retrofit (PBR) approach for long-span truss bridges that are vulnerable to sudden member-loss scenarios. The performance of the bridge has been evaluated by using the demand-to-capacity ratio (DCR) or strain ratio (SR) on the member/component level or the displacement factor on the bridge system level as indicators. Based on the analysis results, the argument is made that the proposed PBR approach allows bridge designers to meet the predetermined performance objectives for sudden member-loss loading conditions. Increase in weight of steel because of such the ALP retrofits is less than 10%. The retrofitted bridge would meet the desired performance levels in the event of sudden loss of any members on the primary trusses of the bridge.