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.

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.

A Lightweight UAV Visual Obstacle Avoidance Algorithm Based on Improved YOLOv8

The importance of unmanned aerial vehicle(UAV)obstacle avoidance algorithms lies in their ability to ensure flight safety and collision avoidance,thereby protecting people and property.We propose UAD-YOLOv8,a lightweight YOLOv8-based obstacle detection algorithm optimized for UAV obstacle avoidance.The algorithm enhances the detection capability for small and irregular obstacles by removing the P5 feature layer and introducing deformable convolution v2(DCNv2)to optimize the cross stage partial bottleneck with 2 convolutions and fusion(C2f)module.Additionally,it reduces the model’s parameter count and computational load by constructing the unite ghost and depth-wise separable convolution(UGDConv)series of lightweight convolutions and a lightweight detection head.Based on this,we designed a visual obstacle avoidance algorithm that can improve the obstacle avoidance performance of UAVs in different environments.In particular,we propose an adaptive distance detection algorithm based on obstacle attributes to solve the ranging problem for multiple types and irregular obstacles to further enhance the UAV’s obstacle avoidance capability.To verify the effectiveness of the algorithm,the UAV obstacle detection(UAD)dataset was created.The experimental results show that UAD-YOLOv8 improves mAP50 by 3.4%and reduces GFLOPs by 34.5%compared to YOLOv8n while reducing the number of parameters by 77.4%and the model size by 73%.These improvements significantly enhance the UAV’s obstacle avoidance performance in complex environments,demonstrating its wide range of applications.

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.

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.

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.

Effects of Continuous Cropping on Soil Microbial Flora and Research Progress of Continuous Cropping Obstacle Reduction Techniques

Continuous cropping can bring economic benefits in a short time and meet the growing demand of agricultural products such as grain,but long-term continuous cropping will accelerate soil degradation,lead to the reduction of crop yield and the increase of disease rate,and destroy the balance of soil microbial structure.Therefore,it is not conducive to the sustainable development of soil ecosystem.In this paper,the problems caused by continuous cropping,such as imbalance of soil microbial flora,decrease of biodiversity,accumulation of root exudates and their effects on soil fertility and crop growth,were summarized,and some measures were suggested to alleviate the obstacles of continuous cropping,such as reasonable rotation,adjustment of intercropping planting mode and application of biological fertilizers.Moreover,the paper also looked forward to the development trend of continuous cropping obstacle reduction techniques,including the integration and application of biological techniques,the promotion of green ecological techniques and the application of intelligent management system.This study provides theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promote the healthy and sustainable development of modern agriculture.

Impact of Continuous Cropping on Soil Phenolic Acid Substances and Research Progress on Continuous Cropping Obstacle Reduction Techniques

At present,long-term continuous cropping in agricultural production has formed a relatively common development trend.With the increase of continuous cropping years,soil phenolic acids are also affected to varying degrees.This paper summarized the effects of continuous cropping on soil phenolic acids and the research progress of continuous cropping obstacle reduction techniques,aiming at providing theoretical basis and technical support for the research of continuous cropping obstacle reduction techniques and promoting the healthy and sustainable development of modern agriculture.

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.

Effects of Different Fertilization Treatments on Soil Microbial Biomass,Soil Enzyme Activities and Related Nutrients in Continuous-cropping Sugarcane Field

[Objective] This study was conducted to expound the fertility improvement effect in continuous-cropping sugarcane field and provide reference for establishment of rational sugarcane fertilization system and improvement of soil quality in continuous-cropping sugarcane field. [Method] The soil in the experimental region is latosolic red soil which was planted with sugarcane for 11 years continuously, and 8 treatments including sole application of chemical fertilizers, sole application of organ- ic fertilizer, and combined application of organic fertilizer and chemical fertilizers were designed according to different fertilization measures. The effects of different fertilization treatments on soil microbial biomass, soil enzyme activities and related fertility factors were determined. [Result} Different fertilization treatments all showed soil microbial biomass N, C and P and activities of soil acid phosphatase, catalase, sucrase and urease higher than the CK. Soil microbial biomass N increased by 5.56%-67.13%, soil microbial biomass C increased by 4.01%-20.40%, and soil mi- crobial biomass P increased by 6.39%-67.02%. The activity of acid phosphatase was improved by 12.96%-35.19%, the activity of catalase was improved by 18.24% -78.93%, the activity of sucrase was improved by 3.00%-42.00%, and the activity of urease was improved by 1.21%-23.43%. However, the soil nutrients of different fertilization treatments increased non-significantly （P〉0.05）. Soil microbial biomass N, C and P and activities of acid phosphatase, catalase and urease were in significant （P〈0.05） or very significant correlation （P〈0.01） with contents of soil rapidly available P, rapidly available K and total N. [Conclusion] The evaluation of improvement of soil fertility in continuous-cropping sugarcane field using soil microbial biomass and enzyme activities as indexes is more comprehensive and sensitive.

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.

MODELING OF ROBOT MANIPULATOR AND OBSTACLE AVOIDANCE

A robot intelligent path planning system RIPPS is developed, which can be utilized for a robot off line programming tool. The system consists of three parts: geometric modeler, kinematic modeler and path planer. The geometric modeler is used to construct the robot working environment cluttered with obstacles and the robot kinematic modeler to define robot manipulators by the input parameters. Giving robot start and the goal configurations, the path planer can produce a quasi optimal path. By transforming obstacles into the C space to form C obstacles, the path searching is performed in C space. The planning simulations are performed on a SGI workstation, the future research is to implement the planer on a commercial robot manipulators.

The Obstacles and Solutions to Improving Non English-major Students' Listening Comprehension

Listening has been playing an essential role in daily communication.However,listening is the most difficult part and has been an obstacle in the process of learning English for most of learners for a variety of reasons.The paper mainly discusses the linguistic and non—linguistic obstacles in the process of listening and aims to help English learners find out their own shortcomings and put forward some corresponding solutions to improve learners' listening ability.

A Research on Middle School Students'English Reading Obstacles and Strategies

English reading,a key procedure of English learning and teaching in middle school,is an essential way of getting information from the globe and communicating with others.Therefore,efficient comprehension on reading materials will directly serve for accepting the information.And it is extremely important for middle school students to acquire certain reading ability.At present,great attention has been paid to the course of reading in the instruction of English by the Chinese Education Department.But middle school students'read ing ability is still much lower than the target they should reach because of a set of existing obstacles that prevent them from being effective English readers.What are these obstacles? How to break them down? This paper will first point out and then analyze the obstacles that af fect middle school students'reading ability from two aspects:linguistic obstacles(obstacles of lexicon,grammar and background knowl edge) and non-linguistic obstacles(obstacles of psychology,interest,skill,and habit).After demonstrating different obstacles,the paper also come up with some corresponding strategies in the hope of helping middle school students to be effective English readers.

The Obstacles in Cross-cultural Communication

In Cross-cultural communication,the ability of the languages and the ability of the cultures are the crucial factors in the communicating activities.People with the same cultural background communicate with each other easily and smoothly,and understand each other better,and there are fewer or no obstacles in their communication at all.The different cultural backgrounds and traditions,the different social customs and everyday living habits,and the different values all will affect the communication quality and will surely result in obstacles in cross-cultural communication. The obstacles which frequently occur in the cross-cultural communication are:ethnocentrism,stereotyping, prejudice,and the different cultural backgrounds.In order to do away with the obstacles and to make the communication smoothly and successfully,the communicating parties both should observe the cooperative principles and politeness principles.And what's more,they must discard their own prejudices,and respect others,together to fulfill the cross-cultural communicating activities.

LOCAL REGULARITY RESULT FOR SOLUTIONS OF OBSTACLE PROBLEMS

This paper gives the local regularity result for solutions to obstacle problems of A-harmonic equation divA(x, ξu(x)) = 0, |A.(x,ξ)|≈|?|p-1, when 1 < p < n and the obstacle function (?)≥0.

Distributed formation control for a multi-agent system with dynamic and static obstacle avoidances

Formation control and obstacle avoidance for multi-agent systems have attracted more and more attention. In this paper, the problems of formation control and obstacle avoidance are investigated by means of a consensus algorithm. A novel distributed control model is proposed for the multi-agent system to form the anticipated formation as well as achieve obstacle avoidance. Based on the consensus algorithm, a distributed control function consisting of three terms （formation control term, velocity matching term, and obstacle avoidance term） is presented. By establishing a novel formation control matrix, a formation control term is constructed such that the agents can converge to consensus and reach the anticipated formation. A new obstacle avoidance function is developed by using the modified potential field approach to make sure that obstacle avoidance can be achieved whether the obstacle is in a dynamic state or a stationary state. A velocity matching term is also put forward to guarantee that the velocities of all agents converge to the same value. Furthermore, stability of the control model is proven. Simulation results are provided to demonstrate the effectiveness of the proposed control.

Application of A* Algorithm for Real-time Path Re-planning of an Unmanned Surface Vehicle Avoiding Underwater Obstacles

This paper describes path re-planning techniques and underwater obstacle avoidance for unmanned surface vehicle(USV) based on multi-beam forward looking sonar(FLS). Near-optimal paths in static and dynamic environments with underwater obstacles are computed using a numerical solution procedure based on an A* algorithm. The USV is modeled with a circular shape in 2 degrees of freedom(surge and yaw). In this paper, two-dimensional(2-D) underwater obstacle avoidance and the robust real-time path re-planning technique for actual USV using multi-beam FLS are developed. Our real-time path re-planning algorithm has been tested to regenerate the optimal path for several updated frames in the field of view of the sonar with a proper update frequency of the FLS. The performance of the proposed method was verified through simulations, and sea experiments. For simulations, the USV model can avoid both a single stationary obstacle, multiple stationary obstacles and moving obstacles with the near-optimal trajectory that are performed both in the vehicle and the world reference frame. For sea experiments, the proposed method for an underwater obstacle avoidance system is implemented with a USV test platform. The actual USV is automatically controlled and succeeded in its real-time avoidance against the stationary undersea obstacle in the field of view of the FLS together with the Global Positioning System(GPS) of the USV.

Reinforcement Learning Based Obstacle Avoidance for Autonomous Underwater Vehicle

Obstacle avoidance becomes a very challenging task for an autonomous underwater vehicle(AUV)in an unknown underwater environment during exploration process.Successful control in such case may be achieved using the model-based classical control techniques like PID and MPC but it required an accurate mathematical model of AUV and may fail due to parametric uncertainties,disturbance,or plant model mismatch.On the other hand,model-free reinforcement learning(RL)algorithm can be designed using actual behavior of AUV plant in an unknown environment and the learned control may not get affected by model uncertainties like a classical control approach.Unlike model-based control model-free RL based controller does not require to manually tune controller with the changing environment.A standard RL based one-step Q-learning based control can be utilized for obstacle avoidance but it has tendency to explore all possible actions at given state which may increase number of collision.Hence a modified Q-learning based control approach is proposed to deal with these problems in unknown environment.Furthermore,function approximation is utilized using neural network(NN)to overcome the continuous states and large statespace problems which arise in RL-based controller design.The proposed modified Q-learning algorithm is validated using MATLAB simulations by comparing it with standard Q-learning algorithm for single obstacle avoidance.Also,the same algorithm is utilized to deal with multiple obstacle avoidance problems.