Path-Following Control With Obstacle Avoidance of Autonomous Surface Vehicles Subject to Actuator Faults

This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.

Potential Benefits and Obstacles of the Use of Internet of Things in Saudi Universities: Empirical Study

Internet of Things (IoT) among of all the technology revolutions has been considered the next evolution of the internet. IoT has become a far more popular area in the computing world. IoT combined a huge number of things (devices) that can be connected through the internet. The purpose: this paper aims to explore the concept of the Internet of Things (IoT) generally and outline the main definitions of IoT. The paper also aims to examine and discuss the obstacles and potential benefits of IoT in Saudi universities. Methodology: the researchers reviewed the previous literature and focused on several databases to use the recent studies and research related to the IoT. Then, the researchers also used quantitative methodology to examine the factors affecting the obstacles and potential benefits of IoT. The data were collected by using a questionnaire distributed online among academic staff and a total of 150 participants completed the survey. Finding: the result of this study reveals there are twelve factors that affect the potential benefits of using IoT such as reducing human errors, increasing business income and worker’s productivity. It also shows the eighteen factors which affect obstacles the IoT use, for example sensors’ cost, data privacy, and data security. These factors have the most influence on using IoT in Saudi universities.

Effect of a static pedestrian as an exit obstacle on evacuation

Building exit as a bottleneck structure is the last and the most congested stage in building evacuation.It is well known that obstacles at the exit affect the evacuation process,but few researchers pay attention to the effect of stationary pedestrians(the elderly with slow speed,the injured,and the static evacuation guide)as obstacles at the exit on the evacuation process.This paper explores the influence of the presence of a stationary pedestrian as an obstacle at the exit on the evacuation from experiments and simulations.We use a software,Pathfinder,based on the agent-based model to study the effect of ratios of exit width(D)to distance(d)between the static pedestrian and the exit,the asymmetric structure by shifting the static pedestrian upward,and types of obstacles on evacuation.Results show that the evacuation time of scenes with a static pedestrian is longer than that of scenes with an obstacle due to the unexpected hindering effect of the static pedestrian.Different ratios of D/d have different effects on evacuation efficiency.Among the five D/d ratios in this paper,the evacuation efficiency is the largest when d is equal to 0.75D,and the existence of the static pedestrian has a positive impact on evacuation in this condition.The influence of the asymmetric structure of the static pedestrian on evacuation efficiency is affected by D/d.This study can provide a theoretical basis for crowd management and evacuation plan near the exit of complex buildings and facilities.

A Novel Obstacle Avoidance Consensus Control for Multi-AUV Formation System

In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and leader-follower strategy(IAPF-LF). Firstly, the proposed fixed-time control can achieve the desired multi-AUV formation within a fixed settling time in any initial system state. Secondly, an event-triggered communication strategy is developed to govern the communication among AUVs, and the communication energy consumption can be decremented. The time-varying formation obstacle avoidance control algorithm based on IAPF-LF is designed to avoid static and dynamic obstacles, the desired formation is maintained in the presence of external disturbances, and there is no Zeno behavior under the fixed-time event-triggered consensus control strategy.The stability of the system is proved by the Lyapunov function and inequality scaling. Finally, simulation examples and water pool experiments are reported to verify the performance of the proposed theoretical algorithms.

An Evaluation of the Coupling Coordination of Technological Innovation System in China’s Marine Biopharmaceutical Industry

The marine biopharmaceutical industry(MBI)has been considered as an important part of the blue economy.The high-quality development of this industry depends on the high-level coordinated development of technological innovation system(TIS).In the present study,the coupling mechanism of industrial innovation input subsystem and innovation output subsystem was analyzed for the first time.On this basis,the development level and coupling coordination level of TIS in China’s MBI during 2008-2018 were empirically evaluated with the capacity coupling coordination model.Then,the obstacle factors were diagnosed and recognized with the obstacle model.The results showed that the innovation input index fluctuated at a low level in China’s MBI.The innovation output index has basically maintained a growth trend,whereas the quality of development was not high.Although the coupling coordination level of TIS showed a positive change as mild disordered→primary coordinated→well-coordinated,the development type of innovation system has changed from the lagging output of innovation into the lagging input of innovation.Insufficient input of innovation factors remained the main obstacle to the improvement of coordination level.Based on the above analysis,suggestions were put forward from the perspectives of policy and fund guarantees to improve the coupling coordination level in China’s MBI.

Effects of Allelochemicals on Root Growth and Pod Yield in Response to Continuous Cropping Obstacle of Peanut

Continuous cropping(CC)obstacle is a major threat in legume crops production;however,the underlying mechanisms concerning the roles allelochemicals play in CC obstacle are poorly understood.The current 2-year study was conducted to investigate the effects of different kinds and concentrations of allelochemicals,p-hydroxybenzoic acid(H),cinnamic acid(C),phthalic acid(P),and their mixtures(M)on peanut root growth and productivity in response to CC obstacle.Treatment with H,C,P,and M significantly decreased the plant height,dry weight of the leaves and stems,number of branches,and length of the lateral stem compared with control.Exogenous application of H,C,P,and M inhibited the peanut root growth as indicated by the decreased root morphological characters.The allelochemicals also induced the cell membrane oxidation even though the antioxidant enzymes activities were significantly increased in peanut roots.Meanwhile,treatment with H,C,P,and M reduced the contents of total soluble sugar and total soluble protein.Analysis of ATPase activity,nitrate reductase activity,and root system activity revealed that the inhibition effects of allelochemicals on peanut roots might be due to the decrease in activities of ATPase and NR,and the inhibition of root system.Consequently,allelochemicals significantly decreased the pod yield of peanut compared with control.Our results demonstrate that allelochemicals play a dominant role in CC obstacle-induced peanut growth inhibition and yield reduction through damaging the root antioxidant system,unbalancing the osmolytes accumulation,and decreasing the activities of root-related enzymes.

Optimisation-based Verification Process of Obstacle Avoidance Systems for Unicycle-like Mobile Robots

This paper presents an optimisatiombased verification process for obstacle avoidance systems of a unicycle-like mobile robot. It is a novel approach for the collision avoidance verification process. Local and global optimisation based verification processes are developed to find the worst-case parameters and the worst-case distance between the robot and an obstacle. The kinematic and dynamic model of the unicycle-like mobile robot is first introduced with force and torque as the inputs. The design of the control system is split into two parts. One is velocity and rotation using the robot dynamics, and the other is the incremental motion planning for robot kinematics. The artificial potential field method is chosen as a path planning and obstacle avoidance candidate technique for verification study as it is simple and widely used. Different optimisation algorithms are applied and compared for the purpose of verification. It is shown that even for a simple case study where only mass and inertia variations are considered, a local optimization based verification method may fail to identify the worst case. Two global optimisation methods have been investigated： genetic algorithms （GAs） and GLOBAL algorithms. Both of these methods successfully find the worst case. The verification process confirms that the obstacle avoidance algorithm functions correctly in the presence of all the possible parameter variations.

Path Planning of UAV by Combing Improved Ant Colony System and Dynamic Window Algorithm

A fusion algorithm is proposed to enhance the search speed of an ant colony system(ACS)for the global path planning and overcome the challenges of the local path planning in an unmanned aerial vehicle(UAV).The ACS search efficiency is enhanced by adopting a 16-direction 24-neighborhood search way,a safety grid search way,and an elite hybrid strategy to accelerate global convergence.Quadratic planning is performed using the moving average(MA)method.The fusion algorithm incorporates a dynamic window approach(DWA)to deal with the local path planning,sets a retracement mechanism,and adjusts the evaluation function accordingly.Experimental results in two environments demonstrate that the improved ant colony system(IACS)achieves superior planning efficiency.Additionally,the optimized dynamic window approach(ODWA)demonstrates its ability to handle multiple dynamic situations.Overall,the fusion optimization algorithm can accomplish the mixed path planning effectively.

A Study on Development of a Hybrid Aerial/Terrestrial Robot System for Avoiding Ground Obstacles by Flight

To date, many studies related to robots have been performed around the world. Many of these studies have assumed operation at locations where entry is difficult, such as disaster sites, and have focused on various terrestrial robots, such as snake-like, humanoid, spider-type, and wheeled units. Another area of active research in recent years has been aerial robots with small helicopters for operation indoors and outdoors. However,less research has been performed on robots that operate both on the ground and in the air. Accordingly, in this paper, we propose a hybrid aerial/terrestrial robot system. The proposed robot system was developed by equipping a quadcopter with a mechanism for ground movement. It does not use power dedicated to ground movement, and instead uses the flight mechanism of the quadcopter to achieve ground movement as well. Furthermore, we addressed the issue of obstacle avoidance as part of studies on autonomous control. Thus, we found that autonomous control of ground movement and flight was possible for the hybrid aerial/terrestrial robot system, as was autonomous obstacle avoidance by flight when an obstacle appeared during ground movement.

Stepping up after spinal cord injury:negotiating an obstacle during walking

Every day walking consists of frequent voluntary modifications in the gait pattern to negotiate obstacles.After spinal cord injury,stepping over an obstacle becomes challenging.Stepping over an obstacle requires sensorimotor transformations in several structures of the brain,including the parietal cortex,premotor cortex,and motor cortex.Sensory information and planning are transformed into motor commands,which are sent from the motor cortex to spinal neuronal circuits to alter limb trajectory,coordinate the limbs,and maintain balance.After spinal cord injury,bidirectional communication between the brain and spinal cord is disrupted and animals,including humans,fail to voluntarily modify limb trajectory to step over an obstacle.Therefore,in this review,we discuss the neuromechanical control of stepping over an obstacle,why it fails after spinal cord injury,and how it recovers to a certain extent.

Finite Element Simulation Analysis of a Novel 3D-FRSPA for Crawling Locomotion

A novel three-dimensional-fiber reinforced soft pneumatic actuator(3D-FRSPA)inspired by crab claw and human hand structure that can bend and deform independently in each segment is proposed.It has an omni-directional bending configuration,and the fibers twined symmetrically on both sides to improve the bending performance of FRSPA.In this paper,the static and kinematic analysis of 3D-FRSPA are carried out in detail.The effects of fiber,pneumatic chamber and segment length,and circular air chamber radius of 3D-FRSPA on the mechanical performance of the actuator are discussed,respectively.The soft mobile robot composed of 3D-FRSPA has the ability to crawl.Finally,the crawling processes of the soft mobile robot on different road conditions are studied,respectively,and the motion mechanism of the mobile actuator is shown.The numerical results show that the soft mobile robots have a good comprehensive performance,which verifies the correctness of the proposedmodel.This work shows that the proposed structures have great potential in complex road conditions,unknown space detection and other operations.

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement Learning Theory

The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.

Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells

This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.

A System of Image Recognition-Based Railway Foreign Object Intrusion Monitoring Design

The monitoring system designed in this paper is on account of YOLOv5(You Only Look Once)to monitor foreign objects on railway tracks and can broadcast the monitoring information to the locomotive in real time.First,the general structure of the system is determined through demand analysis and feasibility analysis,the foreign object intrusion recognition algorithm is designed,and the data set required for foreign object intrusion recognition is made.Secondly,according to the functional demands,the system selects a suitable neural web,and the programming is reasonable.At last,the system is simulated to validate its functionality(identification and classification of track intrusion and determination of a safe operating zone).

LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.

Facilitating and hindering factors of community nurses'emergency and critical care treatment abilities:A qualitative study

BACKGROUND This study adopts a descriptive phenomenological approach to investigate the facilitators and barriers of community nurses'abilities in managing critical and emergency conditions.With the transition of healthcare systems to the community,the evolution of nursing practices,and the attention from policies and practices,community nurses play a crucial role in the management of critical and emergency conditions.However,there is still a lack of comprehensive understanding regarding the factors that promote or hinder their capabilities in this area.AIM To understand the facilitators and barriers of community nurses in managing critical and emergency conditions,exploring the fundamental reasons and driving forces influencing their treatment capabilities.METHODS This study utilized the destination sampling method between May 2023 and July 2023.It employed a descriptive phenomenological approach within qualitative research methodologies.Through objective sampling,17 community nurses from 7 communities in Changning District,Shanghai,were selected as the study subjects.Semi-structured interviews were conducted to gather data,which were subsequently organized and analyzed using Colaizzi's seven-step analysis method,leading to the extraction of final themes.RESULTS The barrier factors identified from the interviews encompassed three topics:resource allocation,professional factors,and personal literacy.The facilitators comprised three themes:professionalism,management attention,and training and continuing education.We identified that the root causes of the barriers included the lack of practical treatment experience among community nurses,insufficient awareness of self-directed learning,and limited knowledge and technical proficiency.The professional quality of community nurses and management attention serve as motivation for them to enhance their treatment abilities.CONCLUSION To enhance the capability of community nurses in treating acute and critical patients,it is recommended to bolster training specifically tailored to acute and critical care,raise awareness of first aid practices,and elevate knowledge and skill levels.

Research Progress on Effects of Continuous Cropping on Soil Microbial Florae and Its Restoration

Continuous cropping has become a common form of agricultural production at present, but with the increase of continuous cropping years, continuous cropping obstacles such as soil-borne diseases and plant growth potential decline are becoming more and more common. At present, the causes of continuous cropping obstacles and continuous cropping restoration have become a hot issue in agricultural research. This paper summarized the effects of continuous cropping obstacles on soil microbial community structure and main technical methods to repair continuous cropping obstacles, such as agricultural measure management, microbial balance adjustment and soil improvement, aiming to provide theoretical reference for protecting the sustainable utilization of soil ecosystem and ensuring the stability of crop production.

Coordinated Development of Population, Economy and Environment System and Diagnosis of Its Obstacle Factors in Nanjing

Promoting the coordinated development of regional population,economy and environment is beneficial to the realization of sustainable development.Based on the construction of evaluation index system of coordinated development of systems,the entropy weight-TOPSIS method and coupling coordination model,the coordinated development degree of population,economy and environment system in Nanjing was measured,and the temporal variation characteristics of each subsystem and their coordinated development degree form 1997 to 2016 were analyzed.The results showed that the development of population,economy system and environment system in Nanjing was generally in a continuous upward trend.Among them,the economy system developed fastest.The coordinated development degree of population,economy system and environment system in Nanjing was constantly increasing but still at a low level;the degree was only in the primary coordination phase,and its type was environment lagging.The economy subsystem and environment subsystem were important factors restricting the development of population,economy and environment in Nanjing,and the main obstacle factor was the production of industrial solid waste.The results above can provide a scientific basis for promoting the coordinated development of population,economy and environment system in Nanjing and achieving regional sustainable development.

ASSESSMENT OF MILITARY AIRFIELD OBSTACLE FREE SPACE BASED ON GIS

A mathematical model of obstacle limit surfaces for military airfield obstacle free space is established through airfield obstacle free space analysis.Based on the model,triangle mesh elevation model of military airfield obstacle free space is built by using the software-ArcGIS,and the 3-D display result is obtained.It is convenient to evaluate military airfield obstacle for superimposing digital elevation model（DEM）with military airfield topographic map.Thus it improves the efficiency greatly.It lays the foundation for the application of geographic information systems（GIS）in the management of military airfield obstacle free space.

Analysis of the Causes of Continuous Cropping Obstacles for Atractylodes macrocephala Koidz in Pingjiang County and Its Control Methods

First at all, it introduced the concept and the damages of continuous cropping obstacle. Then, it analyzed the causes of continuous cropping obstacles for Atractylodes macrocephala Koidz. In the end, in order to provide guidance for pro- moting sustainable development of Atractylodes macrocephala Koidz industry in Pingjiang County, it put forward some control methods for eliminating continuous cropping obstacles of Atractylodes macrocephala Koidz, including breeding varieties with high resistance; applying rotation cropping and intercropping reasonable; rational fertilization and soil disinfection; introducing antagonistic bacterial and eliminating au- tointoxication.