A great number of visual simultaneous localization and mapping(VSLAM)systems need to assume static features in the environment.However,moving objects can vastly impair the performance of a VSLAM system which relies on...A great number of visual simultaneous localization and mapping(VSLAM)systems need to assume static features in the environment.However,moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption.To cope with this challenging topic,a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed.To reduce the influence of dynamic content,we incorporate the deep-learning-based object detection method in the visual odometry,then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system.Experiment with both on the TUM and KITTI benchmark dataset,as well as in a real-world environment,the results clarify that our method can significantly reduce the tracking error or drift,enhance the robustness,accuracy and stability of the VSLAM system in dynamic scenes.展开更多
While different species in nature have safely solved the problem of navigation in a dynamic environment, this remains a challenging task for researchers around the world. The paper addresses the problem of autonomous ...While different species in nature have safely solved the problem of navigation in a dynamic environment, this remains a challenging task for researchers around the world. The paper addresses the problem of autonomous navigation in an unknown dynamic environment for a single and a group of three wheeled omnidirectional mobile robots(TWOMRs). The robot has to track a dynamic target while avoiding dynamic obstacles and dynamic walls in an unknown and very dense environment. It adopts a behavior-based controller that consists of four behaviors: "target tracking", "obstacle avoidance", "dynamic wall following" and "avoid robots". The paper considers the problem of kinematic saturation. In addition, it introduces a strategy for predicting the velocity of dynamic obstacles based on two successive measurements of the ultrasonic sensors to calculate the velocity of the obstacle expressed in the sensor frame. Furthermore, the paper proposes a strategy to deal with dynamic walls even when they have U-like or V-like shapes. The approach can also deal with the formation control of a group of robots based on the leader-follower structure and the behavior-based control, where the robots have to get together and maintain a given formation while navigating toward the target, avoiding obstacles and walls in a dynamic environment. The effectiveness of the proposed approaches is demonstrated via simulation.展开更多
Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment perception.To adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation...Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment perception.To adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation models to eliminate these moving obstacles.However,these moving obstacle segmentation methods cost too much computation resource for the onboard processing of mobile robots.In the current industrial environment,mobile robot collaboration scenario,the noise of mobile robots could be easily found by on‐board audio‐sensing processors and the direction of sound sources can be effectively acquired by sound source estimation algorithms,but the distance estimation of sound sources is difficult.However,in the field of visual perception,the 3D structure information of the scene is relatively easy to obtain,but the recognition and segmentation of moving objects is more difficult.To address these problems,a novel vision‐audio fusion method that combines sound source localisation methods with a visual SLAM scheme is proposed,thereby eliminating the effect of dynamic obstacles on multi‐agent systems.Several heterogeneous robots experiments in different dynamic scenes indicate very stable self‐localisation and environment reconstruction performance of our method.展开更多
To tackle the problem of simultaneous localization and mapping(SLAM) in dynamic environments, a novel algorithm using landscape theory of aggregation is presented. By exploiting the coherent explanation how actors for...To tackle the problem of simultaneous localization and mapping(SLAM) in dynamic environments, a novel algorithm using landscape theory of aggregation is presented. By exploiting the coherent explanation how actors form alignments in a game provided by the landscape theory of aggregation, the algorithm is able to explicitly deal with the ever-changing relationship between the static objects and the moving objects without any prior models of the moving objects. The effectiveness of the method has been validated by experiments in two representative dynamic environments: the campus road and the urban road.展开更多
This paper presents a visual simultaneous localization and mapping(SLAM)system designed for highly dynamic environments,capable of eliminating dynamic objects using only visual information.The proposed system integrat...This paper presents a visual simultaneous localization and mapping(SLAM)system designed for highly dynamic environments,capable of eliminating dynamic objects using only visual information.The proposed system integrates learning-based and geometry-based methods to address the challenges posed by moving objects.The learning-based approach leverages image segmentation to remove previously trained objects,whereas the geometry-based approach utilises point correlation to eliminate unseen objects.By complementing each other,these methods enhance the robustness of the SLAM system in dynamic sce-narios.Experimental results demonstrate that the proposed method effectively removes dynamic objects.Comparative studies with state-of-the-art algorithms further show that the proposed method achieves superior accuracy and robustness.展开更多
This paper presents a visual simultaneous localization and mapping(SLAM)system designed for highly dynamic environments,capable of eliminating dynamic objects using only visual information.The proposed system integrat...This paper presents a visual simultaneous localization and mapping(SLAM)system designed for highly dynamic environments,capable of eliminating dynamic objects using only visual information.The proposed system integrates learning-based and geometry-based methods to address the challenges posed by moving objects.The learning-based approach leverages image segmentation to remove previously trained objects,whereas the geometry-based approach utilises point correlation to eliminate unseen objects.By complementing each other,these methods enhance the robustness of the SLAM system in dynamic scenarios.Experimental results demonstrate that the proposed method effectively removes dynamic objects.Comparative studies with state-of-the-art algorithms further show that the proposed method achieves superior accuracy and robustness.展开更多
BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons comb...BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.展开更多
Grouting represents a reliable method for strengthening fractured rock masses and preventing seawater infiltration in subsea tunnel engineering. However, grouting composites are continuously subjected to harsh marine ...Grouting represents a reliable method for strengthening fractured rock masses and preventing seawater infiltration in subsea tunnel engineering. However, grouting composites are continuously subjected to harsh marine environments,experiencing both chemical and physical effects from high-concentration erosive seawater ions, elevated water pressure, and complex flow fields. This multi-factor erosion deterioration diminishes the waterproofing capabilities of grouting composites and threatens the service life of subsea tunnel linings. To investigate the erosion deteriortion mechanism induced by sulfate, erosion weakening experiments were conducted using a seawater flow simulation device. The research examined the compressive strength and permeability coefficient of grouting composites under different erosion durations, water-cement ratios, and grouting pressures. In the later stages of the experiment, the strength of grouting composites in the static water erosion control group(SEG) and dynamic water erosion group(DEG) decreased by 31.2% and 18.8%, respectively, compared to the freshwater control group(FG). Futhermore, the permeability coefficient exhibited significant increases. Subsequent microscopic analyses of the eroded grouting composites were performed. This research elucidated the erosion-weakening mechanism of grouting composites subjected to sulfate-induced degradation in complex marine environments. The study emphasizes the critical role of erosion resistance and durability in design and implementation. From practical perspective, this work establishes a foundation for developing enhanced strategies to improve the long-term performance and integrity of grouting composites in subsea tunnel applications.展开更多
Traditional simultaneous localization and mapping(SLAM) mostly performs under the assumption of an ideal static environment, which is not suitable for dynamic environments in the real world. Dynamic real-time object-a...Traditional simultaneous localization and mapping(SLAM) mostly performs under the assumption of an ideal static environment, which is not suitable for dynamic environments in the real world. Dynamic real-time object-aware SLAM(DRO-SLAM) is proposed in this paper, which is a visual SLAM that can realize simultaneous localizing and mapping and tracking of moving objects indoor and outdoor at the same time. It can use target recognition, oriented fast and rotated brief(ORB) feature points, and optical flow assistance to track multi-target dynamic objects and remove them during dense point cloud reconstruction while estimating their pose. By verifying the algorithm effect on the public dataset and comparing it with other methods, it can be obtained that the proposed algorithm has certain guarantees in real-time and accuracy, it also provides more functions. DRO-SLAM can provide the solution to automatic navigation which can realize lightweight deployment, provide more vehicles, pedestrians and other environmental information for navigation.展开更多
This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary obj...This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.展开更多
Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based o...Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper.The algorithm is based on external elite archive and Pareto dominance,and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm.Average entropy and cubic chaoticmapping initialization strategies are proposed to increase population diversity.In the proposed method,we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.Unlike traditional models,this work takes the transmission losses as an optimization target and overcomes complex model constraints through a dynamic relaxation constraint approach.To solve the uncertainty caused by integrating wind and photovoltaic energy in power system scheduling,a multi-objective dynamic environment economical dispatch model is set up that takes the system spinning reserve and network highest losses into account.In this paper,the DE algorithm is improved to form the DGAGE algorithm for the objective optimization of the overall power system,The DE algorithm part of DGAGE is combined with the JAYA algorithm to form the system scheduling HDJ algorithm for multiple energy sources connected to the grid.The effectiveness of the proposed method is demonstrated using CEC2022 and CEC2005 test functions,showing robust optimization performance.Validation on a classical 10-unit system confirms the feasibility of the proposed algorithm in addressing power system scheduling issues.This approach provides a novel solution for dynamic power dispatch systems.展开更多
Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process.Collaborative behavior of a ...Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process.Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved.In this paper,we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems.The proposed decentralized decision-making dynamic area coverage(DDMDAC)method utilizes reinforcement learning(RL)where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment.Intelligent agents increase their global observations by gathering information about the environment by connecting with other agents.The connectivity provides a consensus for the decision-making process,while each agent takes decisions.At each step,agents acquire all reachable agents’states,determine the optimum location for maximal area coverage and receive reward using the covered rate on the target area,respectively.The method was tested in a multi-agent actor-critic simulation platform.In the study,it has been considered that each UAV has a certain communication distance as in real applications.The results show that UAVs with limited communication distance can act jointly in the target area and can successfully cover the area without guidance from the central command unit.展开更多
Coal and gas outburst is an extremely complex dynamic disaster in coal mine production process which will damage casualties and equipment facilities, and disorder the ventilation system by suddenly ejecting a great am...Coal and gas outburst is an extremely complex dynamic disaster in coal mine production process which will damage casualties and equipment facilities, and disorder the ventilation system by suddenly ejecting a great amount of coal and gas into roadway or working face. This paper analyzed the interaction among the three essential elements of coal and gas outburst dynamic system. A stress-seepage-damage coupling model was established which can be used to simulate the evolution of the dynamical system, and then the size scale of coal and gas outburst dynamical system was investigated. Results show that the dynam- ical system is consisted of three essential elements, coal-gas medium （material basis）, geology dynamic environment （internal motivation） and mining disturbance （external motivation）. On the case of CI 3 coal seam in Panyi Mine, the dynamical system exists in the range of 8-12 m in front of advancing face. The size scale will be larger where there are large geologic structures. This research plays an important guid- ing role for developing measures of coal and gas outburst prediction and prevention.展开更多
The grain-size distribution of surface sediments in the Bohai Sea(BS) and the northern Yellow Sea(NYS), and its relationship with sediment supply and hydrodynamic environment were investigated based on grain-size comp...The grain-size distribution of surface sediments in the Bohai Sea(BS) and the northern Yellow Sea(NYS), and its relationship with sediment supply and hydrodynamic environment were investigated based on grain-size compositions of surface sediments and modern sedimentation rates. The results showed that the surface sediments in the BS and the NYS were primarily composed of silty sand and clayey silt with a dominant size of silt. In addition, the Yellow River delivered high amount of water and sediments to the BS, and they are dominated in surface sediments(mainly silt) in the Bohai Bay, the Yellow River mouth, the center of the BS, and the north coast of Shandong Peninsula. The coarse-grained sediments were mainly deposited at the river mouth due to the estuarine filtration and physical sorting. Meanwhile, there was a significant relationship among the modern sedimentation rate, the surface sediment grain size distribution and sediment transport pattern. The areas with coarser surface sediments generally corresponded low sedimentation rates because of strong erosion;whereas the sedimentation rate was relatively high at the place that the surface sediments were fine-grained. Furthermore, the grain-size trend analysis showed that the areas with fine-grained surface sediments such as the mud area in the central BS and the upper Liaodong Bay were the convergent centers of surface sediments, except for the Bohai Bay and the subaqueous Yellow River Delta where offshore sediment transport was evident.展开更多
This study presents a statistical landslide susceptibility assessment(LSA) in a dynamic environment. The study area is located in the eastern part of Lanzhou, NW China. The Lanzhou area has exhibited rapid urbanizatio...This study presents a statistical landslide susceptibility assessment(LSA) in a dynamic environment. The study area is located in the eastern part of Lanzhou, NW China. The Lanzhou area has exhibited rapid urbanization rates over the past decade associated with greening, continuous land use change, and geomorphic reshaping activities. To consider the dynamics of the environment in the LSA, multitemporal data for landslide inventories and the corresponding causal factors were collected. The weights of evidence(Wof E) method was used to perform the LSA. Three time stamps, i.e., 2000, 2012, and 2016, were selected to assess the state of landslide susceptibility over time. The results show a clear evolution of the landslide susceptibility patterns that was mainly governed by anthropogenic activities directed toward generating safer building grounds for civil infrastructure. The low and very low susceptibility areas increased by approximately 10% between 2000 and 2016. At the same time, areas of medium, high and very high susceptibility zones decreased proportionally. Based on the results, an approach to design the statistical LSA under dynamic conditions is proposed, the issues and limitations of this approach are also discussed. The study shows that under dynamic conditions, the requirements for data quantity and quality increase significantly. A dynamic environment requires greater effort to estimate the causal relations between the landslides and controlling factors as well as for model validation.展开更多
A weighted time-based global hierarchical path planning method is proposed to obtain the global optimal path from the starting point to the destination with time optimal control. First, the grid-or graph-based modelin...A weighted time-based global hierarchical path planning method is proposed to obtain the global optimal path from the starting point to the destination with time optimal control. First, the grid-or graph-based modeling is performed and the environment is divided into a set of grids or nodes. Then two time-based features of time interval and time cost are presented. The time intervals for each grid are built, during each interval the condition of the grid remains stable, and a time cost of passing through the grid is defined and assigned to each interval. Furthermore, the weight is introduced for taking both time and distance into consideration, and thus a sequence of multiscale paths with total time cost can be achieved. Experimental results show that the proposed method can handle the complex dynamic environment, obtain the global time optimal path and has the potential to be applied to the autonomous robot navigation and traffic environment.展开更多
In order to solve the problem of path planning of mobile robots in a dynamic environment,an improved rapidly-exploring random tree^(*)(RRT^(*))algorithm is proposed in this paper.First,the target bias sampling is intr...In order to solve the problem of path planning of mobile robots in a dynamic environment,an improved rapidly-exploring random tree^(*)(RRT^(*))algorithm is proposed in this paper.First,the target bias sampling is introduced to reduce the randomness of the RRT^(*)algorithm,and then the initial path planning is carried out in a static environment.Secondly,apply the path in a dynamic environment,and use the initially planned path as the path cache.When a new obstacle appears in the path,the invalid path is clipped and the path is replanned.At this time,there is a certain probability to select the point in the path cache as the new node,so that the new path maintains the trend of the original path to a greater extent.Finally,MATLAB is used to carry out simulation experiments for the initial planning and replanning algorithms,respectively.More specifically,compared with the original RRT^(*)algorithm,the simulation results show that the number of nodes used by the new improved algorithm is reduced by 43.19%on average.展开更多
With the increasing oil demand, the construction of oil energy reserves in China needs to be further strengthened. However, given that there has been no research on the main influencing factors of crude oil temperatur...With the increasing oil demand, the construction of oil energy reserves in China needs to be further strengthened. However, given that there has been no research on the main influencing factors of crude oil temperature drop in storage tanks under actual dynamically changing environments, this paper considers the influence of dynamic thermal environment and internal crude oil physical properties on the fluctuating changes in crude oil temperature. A theoretical model of the unsteady-state temperature drop heat transfer process is developed from a three-dimensional perspective. According to the temperature drop variation law of crude oil storage tank under the coupling effect of various heat transfer modes such as external forced convection, thermal radiation, and internal natural convection, the external dynamic thermal environment influence zone, the internal crude oil physical property influence zone, and the intermediate transition zone of the tank are proposed. And the multiple non-linear regression method is used to quantitatively characterize the influence of external ambient temperature, solar radiation, wind speed, internal crude oil density, viscosity, and specific heat capacity on the temperature drop of crude oil in each influencing zone. The results of this paper not only quantitatively explain the main influencing factors of the oil temperature drop in the top, wall, and bottom regions of the tank, but also provide a theoretical reference for oil security reserves under a dynamic thermal environment.展开更多
For safety reasons,in the automated dispensing medicines process,robots and humans cooperate to accomplish the task of drug sorting and distribution.In this dynamic unstructured environment,such as a humanrobot collab...For safety reasons,in the automated dispensing medicines process,robots and humans cooperate to accomplish the task of drug sorting and distribution.In this dynamic unstructured environment,such as a humanrobot collaboration scenario,the safety of human,robot,and equipment in the environment is paramount.In this work,a practical and effective robot motion planning method is proposed for dynamic unstructured environments.To figure out the problems of blind zones of single depth sensor and dynamic obstacle avoidance,we first propose a method for establishing offline mapping and online fusion of multi-sensor depth images and 3D grids of the robot workspace,which is used to determine the occupation states of the 3D grids occluded by robots and obstacles and to conduct real-time estimation of the minimum distance between the robot and obstacles.Then,based on the reactive control method,the attractive and repulsive forces are calculated and transformed into robot joint velocities to avoid obstacles in real time.Finally,the robot’s dynamic obstacle avoidance ability is evaluated on an experimental platform with a UR5 robot and two KinectV2 RGB-D sensors,and the effectiveness of the proposed method is verified.展开更多
A low frequency dynamic environment prediction of spacecraft using dynamic substructu- ring is presented. The dynamic environment could be used to describe the level of the excitation on the spacecraft itself and auxi...A low frequency dynamic environment prediction of spacecraft using dynamic substructu- ring is presented. The dynamic environment could be used to describe the level of the excitation on the spacecraft itself and auxiliary equipment. In addition, the dynamic environment is a criterion for the structural dynamic design as well as the ground verification test. The proposed prediction method could solve two major problems. The first is the time consumption of analyzing the whole spacecraft model due to the huge amount of degrees of freedom, and the second is multi-source for component structural dynamic models from distributive departments. To demonstrate the feasibility and efficien- cy, the proposed prediction method is applied to resolve a launching satellite case, and the results were compared with those obtained by the traditional prediction technology using the finite element method.展开更多
基金the National Natural Science Foundation of China(No.61671470).
文摘A great number of visual simultaneous localization and mapping(VSLAM)systems need to assume static features in the environment.However,moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption.To cope with this challenging topic,a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed.To reduce the influence of dynamic content,we incorporate the deep-learning-based object detection method in the visual odometry,then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system.Experiment with both on the TUM and KITTI benchmark dataset,as well as in a real-world environment,the results clarify that our method can significantly reduce the tracking error or drift,enhance the robustness,accuracy and stability of the VSLAM system in dynamic scenes.
文摘While different species in nature have safely solved the problem of navigation in a dynamic environment, this remains a challenging task for researchers around the world. The paper addresses the problem of autonomous navigation in an unknown dynamic environment for a single and a group of three wheeled omnidirectional mobile robots(TWOMRs). The robot has to track a dynamic target while avoiding dynamic obstacles and dynamic walls in an unknown and very dense environment. It adopts a behavior-based controller that consists of four behaviors: "target tracking", "obstacle avoidance", "dynamic wall following" and "avoid robots". The paper considers the problem of kinematic saturation. In addition, it introduces a strategy for predicting the velocity of dynamic obstacles based on two successive measurements of the ultrasonic sensors to calculate the velocity of the obstacle expressed in the sensor frame. Furthermore, the paper proposes a strategy to deal with dynamic walls even when they have U-like or V-like shapes. The approach can also deal with the formation control of a group of robots based on the leader-follower structure and the behavior-based control, where the robots have to get together and maintain a given formation while navigating toward the target, avoiding obstacles and walls in a dynamic environment. The effectiveness of the proposed approaches is demonstrated via simulation.
基金supported by the Shenzhen Science and Technology Program(JSGG20220606142803007)the Shenzhen Institute of Artificial Intelligence and Robotics for Society(AIRS).
文摘Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment perception.To adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation models to eliminate these moving obstacles.However,these moving obstacle segmentation methods cost too much computation resource for the onboard processing of mobile robots.In the current industrial environment,mobile robot collaboration scenario,the noise of mobile robots could be easily found by on‐board audio‐sensing processors and the direction of sound sources can be effectively acquired by sound source estimation algorithms,but the distance estimation of sound sources is difficult.However,in the field of visual perception,the 3D structure information of the scene is relatively easy to obtain,but the recognition and segmentation of moving objects is more difficult.To address these problems,a novel vision‐audio fusion method that combines sound source localisation methods with a visual SLAM scheme is proposed,thereby eliminating the effect of dynamic obstacles on multi‐agent systems.Several heterogeneous robots experiments in different dynamic scenes indicate very stable self‐localisation and environment reconstruction performance of our method.
基金Project(XK100070532)supported by Beijing Education Committee Cooperation Building Foundation,China
文摘To tackle the problem of simultaneous localization and mapping(SLAM) in dynamic environments, a novel algorithm using landscape theory of aggregation is presented. By exploiting the coherent explanation how actors form alignments in a game provided by the landscape theory of aggregation, the algorithm is able to explicitly deal with the ever-changing relationship between the static objects and the moving objects without any prior models of the moving objects. The effectiveness of the method has been validated by experiments in two representative dynamic environments: the campus road and the urban road.
基金supported by the Autonomous Intelligent Unmanned Systems(No.NSFC 62088101)the National Natural Science Foundation of China(No.62306096)in part by the Zhejiang Provincial Natural Science Foundation of China under Grant(No.LD24F030001).
文摘This paper presents a visual simultaneous localization and mapping(SLAM)system designed for highly dynamic environments,capable of eliminating dynamic objects using only visual information.The proposed system integrates learning-based and geometry-based methods to address the challenges posed by moving objects.The learning-based approach leverages image segmentation to remove previously trained objects,whereas the geometry-based approach utilises point correlation to eliminate unseen objects.By complementing each other,these methods enhance the robustness of the SLAM system in dynamic sce-narios.Experimental results demonstrate that the proposed method effectively removes dynamic objects.Comparative studies with state-of-the-art algorithms further show that the proposed method achieves superior accuracy and robustness.
基金supported by the Autonomous Intelligent Unmanned Systems(No.NSFC 62088101)the National Natural Science Foundation of China(No.62306096)in part by the Zhejiang Provincial Natural Science Foundation of China under Grant(No.LD24F030001).
文摘This paper presents a visual simultaneous localization and mapping(SLAM)system designed for highly dynamic environments,capable of eliminating dynamic objects using only visual information.The proposed system integrates learning-based and geometry-based methods to address the challenges posed by moving objects.The learning-based approach leverages image segmentation to remove previously trained objects,whereas the geometry-based approach utilises point correlation to eliminate unseen objects.By complementing each other,these methods enhance the robustness of the SLAM system in dynamic scenarios.Experimental results demonstrate that the proposed method effectively removes dynamic objects.Comparative studies with state-of-the-art algorithms further show that the proposed method achieves superior accuracy and robustness.
基金Supported by Hangzhou Medical and Health Technology Project,No.OO20191141。
文摘BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 42477194 and 52279115)Fundamental Research Funds for the Central Universities (Grant No. 202441008)。
文摘Grouting represents a reliable method for strengthening fractured rock masses and preventing seawater infiltration in subsea tunnel engineering. However, grouting composites are continuously subjected to harsh marine environments,experiencing both chemical and physical effects from high-concentration erosive seawater ions, elevated water pressure, and complex flow fields. This multi-factor erosion deterioration diminishes the waterproofing capabilities of grouting composites and threatens the service life of subsea tunnel linings. To investigate the erosion deteriortion mechanism induced by sulfate, erosion weakening experiments were conducted using a seawater flow simulation device. The research examined the compressive strength and permeability coefficient of grouting composites under different erosion durations, water-cement ratios, and grouting pressures. In the later stages of the experiment, the strength of grouting composites in the static water erosion control group(SEG) and dynamic water erosion group(DEG) decreased by 31.2% and 18.8%, respectively, compared to the freshwater control group(FG). Futhermore, the permeability coefficient exhibited significant increases. Subsequent microscopic analyses of the eroded grouting composites were performed. This research elucidated the erosion-weakening mechanism of grouting composites subjected to sulfate-induced degradation in complex marine environments. The study emphasizes the critical role of erosion resistance and durability in design and implementation. From practical perspective, this work establishes a foundation for developing enhanced strategies to improve the long-term performance and integrity of grouting composites in subsea tunnel applications.
文摘Traditional simultaneous localization and mapping(SLAM) mostly performs under the assumption of an ideal static environment, which is not suitable for dynamic environments in the real world. Dynamic real-time object-aware SLAM(DRO-SLAM) is proposed in this paper, which is a visual SLAM that can realize simultaneous localizing and mapping and tracking of moving objects indoor and outdoor at the same time. It can use target recognition, oriented fast and rotated brief(ORB) feature points, and optical flow assistance to track multi-target dynamic objects and remove them during dense point cloud reconstruction while estimating their pose. By verifying the algorithm effect on the public dataset and comparing it with other methods, it can be obtained that the proposed algorithm has certain guarantees in real-time and accuracy, it also provides more functions. DRO-SLAM can provide the solution to automatic navigation which can realize lightweight deployment, provide more vehicles, pedestrians and other environmental information for navigation.
基金supported by the National Natural Science Foundation of China(Nos.12272104,U22B2013).
文摘This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.
基金funded by the Major Humanities and Social Sciences Research Projects in Zhejiang Higher Education Institutions,grant number 2023QN131National Innovation Training Program Project in China,grant number 202410451009.
文摘Considering the special features of dynamic environment economic dispatch of power systems with high dimensionality,strong coupling,nonlinearity,and non-convexity,a GA-DE multi-objective optimization algorithm based on dual-population pseudo-parallel genetic algorithm-differential evolution is proposed in this paper.The algorithm is based on external elite archive and Pareto dominance,and it adopts the cooperative co-evolution mechanism of differential evolution and genetic algorithm.Average entropy and cubic chaoticmapping initialization strategies are proposed to increase population diversity.In the proposed method,we analyze the distribution of neighboring solutions and apply a new Pareto solution set pruning approach.Unlike traditional models,this work takes the transmission losses as an optimization target and overcomes complex model constraints through a dynamic relaxation constraint approach.To solve the uncertainty caused by integrating wind and photovoltaic energy in power system scheduling,a multi-objective dynamic environment economical dispatch model is set up that takes the system spinning reserve and network highest losses into account.In this paper,the DE algorithm is improved to form the DGAGE algorithm for the objective optimization of the overall power system,The DE algorithm part of DGAGE is combined with the JAYA algorithm to form the system scheduling HDJ algorithm for multiple energy sources connected to the grid.The effectiveness of the proposed method is demonstrated using CEC2022 and CEC2005 test functions,showing robust optimization performance.Validation on a classical 10-unit system confirms the feasibility of the proposed algorithm in addressing power system scheduling issues.This approach provides a novel solution for dynamic power dispatch systems.
文摘Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process.Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved.In this paper,we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems.The proposed decentralized decision-making dynamic area coverage(DDMDAC)method utilizes reinforcement learning(RL)where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment.Intelligent agents increase their global observations by gathering information about the environment by connecting with other agents.The connectivity provides a consensus for the decision-making process,while each agent takes decisions.At each step,agents acquire all reachable agents’states,determine the optimum location for maximal area coverage and receive reward using the covered rate on the target area,respectively.The method was tested in a multi-agent actor-critic simulation platform.In the study,it has been considered that each UAV has a certain communication distance as in real applications.The results show that UAVs with limited communication distance can act jointly in the target area and can successfully cover the area without guidance from the central command unit.
基金funded by the National Natural Science Foundation of China(No.51674132)the State Key Research Development Program of China(No.2016YFC0801407-2)+2 种基金the Open Projects of State Key Laboratory for Geo Mechanics and Deep Underground Engineering of China(No.SKLGDUEK1510)the Open Projects of State Key Laboratory of Coal Resources and Safe Mining of China(No.SKLCRSM15KF04)the Research Fund of State and Local Joint Engineering Laboratory for Gas Drainage&Ground Control of Deep Mines(Henan Polytechnic University)(No.G201602)
文摘Coal and gas outburst is an extremely complex dynamic disaster in coal mine production process which will damage casualties and equipment facilities, and disorder the ventilation system by suddenly ejecting a great amount of coal and gas into roadway or working face. This paper analyzed the interaction among the three essential elements of coal and gas outburst dynamic system. A stress-seepage-damage coupling model was established which can be used to simulate the evolution of the dynamical system, and then the size scale of coal and gas outburst dynamical system was investigated. Results show that the dynam- ical system is consisted of three essential elements, coal-gas medium （material basis）, geology dynamic environment （internal motivation） and mining disturbance （external motivation）. On the case of CI 3 coal seam in Panyi Mine, the dynamical system exists in the range of 8-12 m in front of advancing face. The size scale will be larger where there are large geologic structures. This research plays an important guid- ing role for developing measures of coal and gas outburst prediction and prevention.
基金supported by the National Natural Science Foundation of China (No.41525021)the Ministry of Science and Technology of People's Republic of China (Nos.2016YFA0600903 and 2017YFC0405502)。
文摘The grain-size distribution of surface sediments in the Bohai Sea(BS) and the northern Yellow Sea(NYS), and its relationship with sediment supply and hydrodynamic environment were investigated based on grain-size compositions of surface sediments and modern sedimentation rates. The results showed that the surface sediments in the BS and the NYS were primarily composed of silty sand and clayey silt with a dominant size of silt. In addition, the Yellow River delivered high amount of water and sediments to the BS, and they are dominated in surface sediments(mainly silt) in the Bohai Bay, the Yellow River mouth, the center of the BS, and the north coast of Shandong Peninsula. The coarse-grained sediments were mainly deposited at the river mouth due to the estuarine filtration and physical sorting. Meanwhile, there was a significant relationship among the modern sedimentation rate, the surface sediment grain size distribution and sediment transport pattern. The areas with coarser surface sediments generally corresponded low sedimentation rates because of strong erosion;whereas the sedimentation rate was relatively high at the place that the surface sediments were fine-grained. Furthermore, the grain-size trend analysis showed that the areas with fine-grained surface sediments such as the mud area in the central BS and the upper Liaodong Bay were the convergent centers of surface sediments, except for the Bohai Bay and the subaqueous Yellow River Delta where offshore sediment transport was evident.
基金the framework of a scientific-technical cooperation project between the Federal Institute for Geosciences and Natural Resources(BGR)and the China Geological Survey(CGS)co-funded by the German Ministry of the Economic Affairs and Energy(BMWi)and Ministry of Land and Resources of the People's Republik of China
文摘This study presents a statistical landslide susceptibility assessment(LSA) in a dynamic environment. The study area is located in the eastern part of Lanzhou, NW China. The Lanzhou area has exhibited rapid urbanization rates over the past decade associated with greening, continuous land use change, and geomorphic reshaping activities. To consider the dynamics of the environment in the LSA, multitemporal data for landslide inventories and the corresponding causal factors were collected. The weights of evidence(Wof E) method was used to perform the LSA. Three time stamps, i.e., 2000, 2012, and 2016, were selected to assess the state of landslide susceptibility over time. The results show a clear evolution of the landslide susceptibility patterns that was mainly governed by anthropogenic activities directed toward generating safer building grounds for civil infrastructure. The low and very low susceptibility areas increased by approximately 10% between 2000 and 2016. At the same time, areas of medium, high and very high susceptibility zones decreased proportionally. Based on the results, an approach to design the statistical LSA under dynamic conditions is proposed, the issues and limitations of this approach are also discussed. The study shows that under dynamic conditions, the requirements for data quantity and quality increase significantly. A dynamic environment requires greater effort to estimate the causal relations between the landslides and controlling factors as well as for model validation.
基金Supported by the National Natural Science Foundation of China(No.61100143,No.61370128)the Program for New Century Excellent Talents in University of the Ministry of Education of China(NCET-13-0659)Beijing Higher Education Young Elite Teacher Project(YETP0583)
文摘A weighted time-based global hierarchical path planning method is proposed to obtain the global optimal path from the starting point to the destination with time optimal control. First, the grid-or graph-based modeling is performed and the environment is divided into a set of grids or nodes. Then two time-based features of time interval and time cost are presented. The time intervals for each grid are built, during each interval the condition of the grid remains stable, and a time cost of passing through the grid is defined and assigned to each interval. Furthermore, the weight is introduced for taking both time and distance into consideration, and thus a sequence of multiscale paths with total time cost can be achieved. Experimental results show that the proposed method can handle the complex dynamic environment, obtain the global time optimal path and has the potential to be applied to the autonomous robot navigation and traffic environment.
基金National Natural Science Foundation of China(No.61903291)。
文摘In order to solve the problem of path planning of mobile robots in a dynamic environment,an improved rapidly-exploring random tree^(*)(RRT^(*))algorithm is proposed in this paper.First,the target bias sampling is introduced to reduce the randomness of the RRT^(*)algorithm,and then the initial path planning is carried out in a static environment.Secondly,apply the path in a dynamic environment,and use the initially planned path as the path cache.When a new obstacle appears in the path,the invalid path is clipped and the path is replanned.At this time,there is a certain probability to select the point in the path cache as the new node,so that the new path maintains the trend of the original path to a greater extent.Finally,MATLAB is used to carry out simulation experiments for the initial planning and replanning algorithms,respectively.More specifically,compared with the original RRT^(*)algorithm,the simulation results show that the number of nodes used by the new improved algorithm is reduced by 43.19%on average.
基金supported by the National Natural Science Foundation of China(52104064)(52074089)the China Postdoctoral Science Foundation(2020M681074)+3 种基金Heilongjiang Provincial Natural Science Foundation of China(YQ2023E006)University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(UNPYSCT-2020152)Postdoctoral Science Foundation of Heilongjiang Province in China(LBH-TZ2106)(LBH-Z20122)Northeast Petroleum University Talents Introduction Fund(2019KQ18).
文摘With the increasing oil demand, the construction of oil energy reserves in China needs to be further strengthened. However, given that there has been no research on the main influencing factors of crude oil temperature drop in storage tanks under actual dynamically changing environments, this paper considers the influence of dynamic thermal environment and internal crude oil physical properties on the fluctuating changes in crude oil temperature. A theoretical model of the unsteady-state temperature drop heat transfer process is developed from a three-dimensional perspective. According to the temperature drop variation law of crude oil storage tank under the coupling effect of various heat transfer modes such as external forced convection, thermal radiation, and internal natural convection, the external dynamic thermal environment influence zone, the internal crude oil physical property influence zone, and the intermediate transition zone of the tank are proposed. And the multiple non-linear regression method is used to quantitatively characterize the influence of external ambient temperature, solar radiation, wind speed, internal crude oil density, viscosity, and specific heat capacity on the temperature drop of crude oil in each influencing zone. The results of this paper not only quantitatively explain the main influencing factors of the oil temperature drop in the top, wall, and bottom regions of the tank, but also provide a theoretical reference for oil security reserves under a dynamic thermal environment.
基金the Interdisciplinary Program of Shanghai Jiao Tong University(No.YG2019QNA25)。
文摘For safety reasons,in the automated dispensing medicines process,robots and humans cooperate to accomplish the task of drug sorting and distribution.In this dynamic unstructured environment,such as a humanrobot collaboration scenario,the safety of human,robot,and equipment in the environment is paramount.In this work,a practical and effective robot motion planning method is proposed for dynamic unstructured environments.To figure out the problems of blind zones of single depth sensor and dynamic obstacle avoidance,we first propose a method for establishing offline mapping and online fusion of multi-sensor depth images and 3D grids of the robot workspace,which is used to determine the occupation states of the 3D grids occluded by robots and obstacles and to conduct real-time estimation of the minimum distance between the robot and obstacles.Then,based on the reactive control method,the attractive and repulsive forces are calculated and transformed into robot joint velocities to avoid obstacles in real time.Finally,the robot’s dynamic obstacle avoidance ability is evaluated on an experimental platform with a UR5 robot and two KinectV2 RGB-D sensors,and the effectiveness of the proposed method is verified.
基金Supported by the Ministerial Level Foundation(2012021)
文摘A low frequency dynamic environment prediction of spacecraft using dynamic substructu- ring is presented. The dynamic environment could be used to describe the level of the excitation on the spacecraft itself and auxiliary equipment. In addition, the dynamic environment is a criterion for the structural dynamic design as well as the ground verification test. The proposed prediction method could solve two major problems. The first is the time consumption of analyzing the whole spacecraft model due to the huge amount of degrees of freedom, and the second is multi-source for component structural dynamic models from distributive departments. To demonstrate the feasibility and efficien- cy, the proposed prediction method is applied to resolve a launching satellite case, and the results were compared with those obtained by the traditional prediction technology using the finite element method.
