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.

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.

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.

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.

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.

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.

Improved RRT^(∗)Algorithm for Automatic Charging Robot Obstacle Avoidance Path Planning in Complex Environments

A new and improved RRT∗algorithm has been developed to address the low efficiency of obstacle avoidance planning and long path distances in the electric vehicle automatic charging robot arm.This algorithm enables the robot to avoid obstacles,find the optimal path,and complete automatic charging docking.It maintains the global completeness and path optimality of the RRT algorithmwhile also improving the iteration speed and quality of generated paths in both 2D and 3D path planning.After finding the optimal path,the B-sample curve is used to optimize the rough path to create a smoother and more optimal path.In comparison experiments,the new algorithmyielded reductions of 35.5%,29.2%,and 11.7%in search time and 22.8%,19.2%,and 9%in path length for the 3D environment.Finally,experimental validation of the automatic charging of electric vehicles was conducted to further verify the effectiveness of the algorithm.The simulation experimental validation was carried out by kinematic modeling and building an experimental platform.The error between the experimental results and the simulation results is within 10%.The experimental results show the effectiveness and practicality of the algorithm.

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.

Flow and clogging in a horizontal silo with a rotary obstacle

The external perturbation applied to a silo and the placement of an immobile obstacle before an exit are two common and effective ways to diminish clogging in the hopper/silo flow.Here,we incorporate the local perturbation into a fixed obstacle,and experimentally explore the effects of a rotary obstacle on clogging and the flowing characteristics in the horizontal silo flow driven by a conveyor belt.Even with a low spin rate,the total blocking probability that a particle constructs a stable blocking arch with its neighbors significantly drops.Correspondingly,the average flow rate of the particles through the exit abruptly rises,at least 1 order of magnitude better than that with an immobile obstacle and approaching the flow rate of continuous flow.The rotation enhances the breakage of clogging arches,which is responsible for improving the flowability in the horizontal silo.In addition,there always exists an optimal obstacle position at which the total blocking probability is minimal and the average flow rate peaks,regardless of the spin rate.Finally,clogging is relieved with the increase of the driving velocity of the conveyor belt,showing a“fast is fast”effect that is opposite to the“fast is slow”effect in other systems such as crowd evacuation and gravity-driven hoppers.

OBSTACLE PROBLEMS ON RCD(K,N)METRIC MEASURE SPACES

In this paper,we solve the obstacle problems on metric measure spaces with generalized Ricci lower bounds.We show the existence and Lipschitz continuity of the solutions,and then we establish some regularities of the free boundaries.

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.

Obstacle avoidance method of three-dimensional obstacle spherical cap

Focusing on obstacle avoidance in three-dimensional space for unmanned aerial vehicle(UAV), the direct obstacle avoidance method in dynamic space based on three-dimensional velocity obstacle spherical cap is proposed, which quantifies the influence of threatening obstacles through velocity obstacle spherical cap parameters. In addition, the obstacle avoidance schemes of any point on the critical curve during the multi-obstacles avoidance are given. Through prediction, the insertion point for the obstacle avoidance can be obtained and the flight path can be replanned. Taking the Pythagorean Hodograph(PH) curve trajectory re-planning as an example, the three-dimensional direct obstacle avoidance method in dynamic space is tested. Simulation results show that the proposed method can realize the online obstacle avoidance trajectory re-planning, which increases the flexibility of obstacle avoidance greatly.

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.

Dynamic obstacles detection of tram based on laser radar

The detection of obstacles in a dynamic environment is a hot and difficult problem.A method of autonomously detecting obstacles based on laser radar is proposed as a safety auxiliary structure of tram.The nearest neighbor method is used for spatial obstacles clustering from laser radar data.By analyzing the characteristics of obstacles,the types of obstacles are determined by time correlation.Experiments were carried out on the developed unmanned aerial vehicle(UAV),and the experimental results verify the effectiveness of the proposed method.

Avoiding Non-Manhattan Obstacles Based on Projection of Spatial Corners in Indoor Environment

Monocular vision-based navigation is a considerable ability for a home mobile robot. However, due to diverse disturbances, helping robots avoid obstacles, especially nonManhattan obstacles, remains a big challenge. In indoor environments, there are many spatial right-corners that are projected into two dimensional projections with special geometric configurations. These projections, which consist of three lines,might enable us to estimate their position and orientation in 3 D scenes. In this paper, we present a method for home robots to avoid non-Manhattan obstacles in indoor environments from a monocular camera. The approach first detects non-Manhattan obstacles. Through analyzing geometric features and constraints,it is possible to estimate posture differences between orientation of the robot and non-Manhattan obstacles. Finally according to the convergence of posture differences, the robot can adjust its orientation to keep pace with the pose of detected non-Manhattan obstacles, making it possible avoid these obstacles by itself. Based on geometric inferences, the proposed approach requires no prior training or any knowledge of the camera’s internal parameters,making it practical for robots navigation. Furthermore, the method is robust to errors in calibration and image noise. We compared the errors from corners of estimated non-Manhattan obstacles against the ground truth. Furthermore, we evaluate the validity of convergence of differences between the robot orientation and the posture of non-Manhattan obstacles. The experimental results showed that our method is capable of avoiding non-Manhattan obstacles, meeting the requirements for indoor robot navigation.

Dynamic A^*path finding algorithm and 3D lidar based obstacle avoidance strategy for autonomous vehicles

This paper presents a novel dynamic A^*path finding algorithm and 3D lidar based local obstacle avoidance strategy for an autonomous vehicle.3D point cloud data is collected and analyzed in real time.Local obstacles are detected online and a 2D local obstacle grid map is constructed at 10 Hz/s.The A^*path finding algorithm is employed to generate a local path in this local obstacle grid map by considering both the target position and obstacles.The vehicle avoids obstacles under the guidance of the generated local path.Experiment results have shown the effectiveness of the obstacle avoidance navigation algorithm proposed.

Effective approach for outdoor obstacle detection by clustering LIDAR data context

A method of environment mapping using laser-based light detection and ranging （LIDAR） is proposed in this paper. This method not only has a good detection performance in a wide range of detection angles, but also facilitates the detection of dynamic and hollowed-out obstacles. Essentially using this method, an improved clustering algorithm based on fast search and discovery of density peaks （CBFD） is presented to extract various obstacles in the environment map. By comparing with other cluster algorithms, CBFD can obtain a favorable number of clusterings automatically. Furthermore, the experiments show that CBFD is better and more robust in functionality and performance than the K-means and iterative self-organizing data analysis techniques algorithm （ISODATA）.