Avoidance Method Research Articles

Design optimization of obstacle avoidance of intelligent building the steel bar by integrating reinforcement learning and BIM technology

In promoting the construction of prefabricated residential buildings in Yunnan villages and towns, the use of precast concrete elements is unstoppable. Due to the dense arrangement of steel bars at the joints of precast concrete elements, collisions are prone to occur, which can affect the stress of the components and even pose certain safety hazards for the entire construction project. Because the commonly used the steel bar obstacle avoidance method based on building information modeling has low adaptation rate and cannot change the trajectory of the steel bar to avoid collision, a multi-agent reinforcement learning-based model integrating building information modeling is proposed to solve the steel bar collision in reinforced concrete frame. The experimental results show that the probability of obstacle avoidance of the proposed model in three typical beam-column joints is 98.45%, 98.62% and 98.39% respectively, which is 5.16%, 12.81% and 17.50% higher than that of the building information modeling. In the collision-free path design of the same object, the research on the path design of different types of precast concrete elements takes about 3–4 minutes, which is far less than the time spent by experienced structural engineers on collision-free path modeling. The experimental results indicate that the model constructed by the research institute has good performance and has certain reference significance.

Lunar Rover Collaborated Path Planning with Artificial Potential Field-Based Heuristic on Deep Reinforcement Learning

The International Lunar Research Station, to be established around 2030, will equip lunar rovers with robotic arms as constructors. Construction requires lunar soil and lunar rovers, for which rovers must go toward different waypoints without encountering obstacles in a limited time due to the short day, especially near the south pole. Traditional planning methods, such as uploading instructions from the ground, can hardly handle many rovers moving on the moon simultaneously with high efficiency. Therefore, we propose a new collaborative path-planning method based on deep reinforcement learning, where the heuristics are demonstrated by both the target and the obstacles in the artificial potential field. Environments have been randomly generated where small and large obstacles and different waypoints are created to collect resources, train the deep reinforcement learning agent to propose actions, and lead the rovers to move without obstacles, finish rovers’ tasks, and reach different targets. The artificial potential field created by obstacles and other rovers in every step affects the action choice of the rover. Information from the artificial potential field would be transformed into rewards in deep reinforcement learning that helps keep distance and safety. Experiments demonstrate that our method can guide rovers moving more safely without turning into nearby large obstacles or collision with other rovers as well as consuming less energy compared with the multi-agent A-Star path-planning algorithm with improved obstacle avoidance method.

Formation control and collision avoidance of unmanned water surface vehicles in maritime environments

The formation control of a team of unmanned water surface vehicles (USVs) experiencing maritime environmental disturbances is investigated. These perturbations include water waves, ocean current, wind gusts, communication and measurement errors, and other unmodeled dynamics that are captured through stochastic noise. A distributed control scheme leveraging local communication among team members is proposed to drive the group towards a set of waypoints while simultaneously achieving a desired spatial configuration and collision avoidance. The exponential mean square convergence of the proposed control scheme is shown under a version of the Lyapunov stability theory adapted to stochastic systems. Closed form expressions are proposed to estimate model parameters from experimental data collected in operating environments. The effectiveness of the proposed formation control scheme and collision avoidance method is assessed through numerical simulations demonstrating the interplay between the control parameters and the intensity of the noise. It also highlight the crucial role of the stochastic noise in resolving potential singularities or deadlocks in the vehicles’ motion , which originate from the collision avoidance forces.

Improved Collision Avoidance Algorithm of Autonomous Rice Transplanter Based on Virtual Goal Point

To ensure the operation safety and efficiency of an autonomous rice transplanter, a path planning method of obstacle avoidance based on the improved artificial potential field is proposed. Firstly, the obstacles are divided into circular or elliptic obstacles according to the difference between the length and width of an obstacle as well as the angle between the vehicle’s forward direction and the length direction of the obstacle. Secondly, improved repulsive fields for circular and elliptic models are developed. To escape the local minimum and goal inaccessibility of the traditional artificial potential field as well as meet the requirements of agronomy and vehicle kinematics constraints, the adaptive setting and adjusting strategy for virtual goal points is proposed according to relative azimuth between obstacle and vehicle. The path smoothing method based on the B-spline interpolation method is presented. Finally, the intelligent obstacle avoidance algorithm is designed, and the path evaluation rule is given to obtain the low-cost, non-collision, smooth and shortest obstacle avoidance path. To verify the effectiveness of the proposed obstacle avoidance algorithm, simulation and field experiments are conducted. Simulation and experimental results demonstrate that the proposed improved collision avoidance algorithm is highly effective and realizable.

Scheduling optimization of tier-captive four-way shuttle-based storage and retrieval systems with multiple lifts

The four-way shuttle-based storage and retrieval system (FSS/RS) handles retrieval transactions through shuttles moving horizontally in four directions and lifts moving vertically. The scheduling process and working route of both are important problems for daily operations. This article constructs a scheduling model for the tier-captive FSS/RS with multiple lifts and designs a two-stage optimization heuristic algorithm (OHA). A heuristic assignment algorithm is proposed to determine the retrieval request sequence, and the route-generation stage adopts an improved A-star algorithm with a multi-phase conflict avoidance method to generate shuttle conflict-free routes. Simulation results demonstrate that OHA can reliably generate high-quality solutions, with a low degree of fluctuation in the results, not exceeding 0.5%. The proposed scheduling method outperforms its competitors in all instances, reducing the makespan by 8%. Moreover, the evidence shows that the proposed method can obtain the most competitive scheduling scheme in FSS/RS with more shuttles and lifts.

MCCA: A Decentralized Method for Collision and Deadlock Avoidance With Nonholonomic Robots

MCCA: A Decentralized Method for Collision and Deadlock Avoidance With Nonholonomic Robots

Face and liveness detection with criminal identification using machine learning and image processing techniques for security system

<p>In the past, real-world photos have been used to train classifiers for face liveness identification since the related face presentation attacks (PA) and real-world images have a high degree of overlap. The use of deep convolutional neural networks (CNN) and real-world face photos together to identify the liveness of a face, however, has received very little study. A face recognition system should be able to identify real faces as well as efforts at faking utilizing printed or digital presentations. A true spoofing avoidance method involves observing facial liveness, such as eye blinking and lip movement. However, this strategy is rendered useless when defending against replay assaults that use video. The anti-spoofing technique consists of two modules: the ConvNet classifier module and the blinking eye module, which measure lip and eye movement. The results of the testing demonstrate that the developed module is capable of identifying various face spoof assaults, including those made with the use of posters, masks, or smartphones. To assess the convolutional features in this study adaptively fused from deep CNN produced face pictures and convolutional layers learned from real-world identification. Extensive tests using intra-database and cross-database scenarios on cutting-edge face anti-spoofing databases including CASIA, OULU, NUAA and replay-attack dataset demonstrate that the proposed solution methods for face liveness detection. The algorithm has a 94.30% accuracy rate.</p>

Deployment of a UAV swarm-based LiFi network in the obstacle-ridden environment: algorithms of finding the path for UAV placement

The subject of this study is unmanned aerial vehicle (UAV)-based wireless networks in an obstacle-ridden environment. The aim of this study is to develop methods and software to ensure reliable LiFi communication using swarm UAVs in an obstacle-ridden environment. The objectives are as follows: 1) to describe the problem of providing a reliable UAV swarm-based LiFi network, requirements for the composition and use of UAVs, and assumptions; 2) to develop the methodology for solving research tasks; 3) to develop the method and algorithms for solving the problem, considering the requirements, assumptions, and practical limitations; 4) to explore the algorithms by developing software for modeling and searching for rational UAV placement to ensure the required UAV-based LiFi network characteristics; 5) to provide experiments and illustrative examples of the developed tool’s application. The following results were obtained. 1) The requirements for the composition and use of UAVs for creating LiFi networks, as well as assumptions and limitations for the methodology development and research task solving. 2) An obstacle avoidance method using the left and right angles algorithm. 3) A method for obstacle avoidance using the controlled waterfall algorithm. 4) A software tool for modeling and searching for rational UAV placement to ensure the required LiFi network characteristics. The tool allows route construction under obstacles in 2D space and a comparison of the developed algorithms for various variants of obstacle placement. Conclusions. The main contribution of this research is a set of methods, algorithms, and software tools for providing communications between two points using LiFi technologies and a swarm of UAVs supporting these communications as transmitters in conditions of mechanical obstacles.

An Improved VO Method for Collision Avoidance of Ships in Open Sea

In order to effectively deal with collisions in various encounter situations in open water environments, a ship collision avoidance model was established, and multiple constraints were introduced into the velocity obstacle method, a method to determine the ship domain by calculating the safe distance of approach was proposed. At the same time, the ship collision avoidance model based on the ship domain is analyzed, and the relative velocity set of the collision cone is obtained by solving the common tangent line within the ellipse. The timing of starting collision avoidance is determined by calculating the ship collision risk, and a method for ending collision avoidance is proposed. Finally, by comparing the simulation experiments of the improved algorithm with those of the traditional algorithm and the actual ship experiment results of manual ship maneuvering, it is shown that the method can effectively avoid collisions based on safe encounter distances that comply with navigation experience in different encounter situations. At the same time, it has better performance in collision avoidance behavior. It has certain feasibility and practical applicability.

Route Planning Algorithms for Unmanned Surface Vehicles (USVs): A Comprehensive Analysis

This review paper provides a structured analysis of obstacle avoidance and route planning algorithms for unmanned surface vehicles (USVs) spanning both numerical simulations and real-world applications. Our investigation encompasses the development of USV route planning from the year 2000 to date, classifying it into two main categories: global and local route planning. We emphasize the necessity for future research to embrace a dual approach incorporating both simulation-based assessments and real-world field tests to comprehensively evaluate algorithmic performance across diverse scenarios. Such evaluation systems offer valuable insights into the reliability, endurance, and adaptability of these methodologies, ultimately guiding the development of algorithms tailored to specific applications and evolving demands. Furthermore, we identify the challenges to determining optimal collision avoidance methods and recognize the effectiveness of hybrid techniques in various contexts. Remarkably, artificial potential field, reinforcement learning, and fuzzy logic algorithms emerge as standout contenders for real-world applications as consistently evaluated in simulated environments. The innovation of this paper lies in its comprehensive analysis and critical evaluation of USV route planning algorithms validated in real-world scenarios. By examining algorithms across different time periods, the paper provides valuable insights into the evolution, trends, strengths, and weaknesses of USV route planning technologies. Readers will benefit from a deep understanding of the advancements made in USV route planning. This analysis serves as a road map for researchers and practitioners by furnishing insights to advance USV route planning and collision avoidance techniques.

Antioxidant and Antibacterial Properties of 1,3-Dihydroxy-,2', 2'-Dimethylpyrano-(5,6)-Xanthone from Streptomyces sp. SU84.

<b>Background and Objective:</b> The SU84 was isolated from the rhizosphere of <i>Curcuma longa</i> and identified to be <i>Streptomyces</i> sp. via analysis of its 16S rDNA sequence, chemotaxonomy and morphology. This study aimed to isolate major compounds from the extract culture of strain SU84 and evaluate their antibacterial activity. <b>Materials and Methods:</b> The TLC and silica gel column chromatography were used to purify major compounds, elucidate 1,3-dihydroxy-,2',2'-dimethylpyrano-(5,6)-xanthone (compound <b>1</b>) and lupeol (compound <b>2</b>) using mass spectrometry and nuclear magnetic resonance. One new chemical, compound <b>1</b>, was first isolated from microbial sources. Antibacterial, antioxidant and cytotoxic properties of these compounds were carried out. <b>Results:</b> Various bioassays showed that compound <b>1</b> displayed antibacterial property against Gram-positive bacteria, with a minimum inhibitory concentration of 8-32 μg/mL and minimum bactericidal concentration of 32-128 μg/mL. In addition, the purified compounds were tested against normal cell lines using tetrazolium assay. The results did not show cytotoxic property against L929 and Vero cells, with IC<sub>50</sub> values of >512.00 μg/mL. Compounds <b>1</b> and <b>2</b> have also antioxidant properties, with IC<sub>50</sub> values of 16.67±7.48 and 38.86±8.45 μg/mL, respectively. <b>Conclusion:</b> The findings suggested that compounds of <i>Streptomyces</i> sp. SU84 displayed antibacterial and antioxidant properties without cytotoxic activity. Extensive studies of compound <b>1</b> may be useful for the advancement of improved methods for avoidance, control and management of bacterial infections and metabolic-related free radical contribution.

Event-triggered error-constrained switching guidance-based marine surface vessel path-following control and collision avoidance

For marine surface vessel with input saturation, model uncertainties, and unknown disturbances, this article proposes a path-following control and collision avoidance method based on error-constrained event-triggered switching line-of-sight guidance. This method can autonomously switch between path-following and collision avoidance modes, constrain the position and heading errors to satisfy safe navigation in confined waters, and reduce the computational frequency of the controller and the mechanical wear of the actuator. In the path-following mode, we construct an asymmetric modified barrier Lyapunov function to constrain the position errors and use the relative threshold event-triggered mechanism to reduce the update frequency of the guidance heading angle. In the collision avoidance mode, static or dynamic obstacles are avoided through the response of collision avoidance radius. In the heading and velocity control design, asymmetric modified barrier Lyapunov function and event-triggered mechanism are also applied, so that the marine surface vessel can track the guided heading angle and meet the heading error-constrained while reducing the update frequency of the controller. The adaptive auxiliary systems are used to compensate for the input saturation, and radial basis function neural networks and adaptive laws are used to approximate the model uncertainties and composite disturbances. According to the Lyapunov stability theory, all signals are semi-globally uniformly ultimately bounded and the Zeno phenomenon is avoided. Finally, the comparative experiment shows the superiority of the designed control strategy.

Paediatric radiation therapy without anaesthesia – Are the children moving?

PurposeChildren who require radiation therapy (RT) should ideally be treated awake, without anaesthesia, if possible. Audiovisual distraction is a known method to facilitate awake treatment, but its effectiveness at keeping children from moving during treatment is not known. The aim of this study was to evaluate intrafraction movement of children receiving RT while awake. MethodsIn this prospective study, we measured the intrafraction movement of children undergoing treatment with fractionated RT, using pre- and post-RT cone beam CT (CBCT) with image matching on bony anatomy. Study CBCTs were acquired at first fraction, weekly during RT, and at last fraction. The primary endpoint was the magnitude of vector change between the pre- and post-RT scans. Our hypothesis was that 90 % of CBCT acquisitions would have minimal movement, defined as <3 mm for head-and-neck (HN) treatments and <5 mm for non-HN treatments. ResultsA total of 65 children were enrolled and had evaluable data across 302 treatments with CBCT acquisitions. Median age was 11 years (range, 2–18; 1st and 3rd quartiles 7 and 14 years, respectively). Minimal movement was observed in 99.4 % of HN treatments and 97.2 % of non-HN treatments. The study hypothesis of >90 % of evaluations having minimal movement was met. Children who were age >11 years moved less at initial evaluation but tended to move more as a course of radiation progressed, as compared to children who were younger. ConclusionChildren receiving RT with audiovisual distraction while awake had small magnitudes of observed intrafraction movement, with minimal movement in >97 % of observed RT fractions. This study validates methods of anaesthesia avoidance using audiovisual distraction for selected children.

A Novel Real-Time Obstacle Avoidance Method in Guidance Layer for AUVs' Path Following

A Novel Real-Time Obstacle Avoidance Method in Guidance Layer for AUVs' Path Following

Development of a novel gantry system for cooperative printing of plastic materials

ABSTRACT It is well known that Additive Manufacturing (AM) is a slow process when compared to conventional manufacturing processes. To address this problem, this paper explores the concept of cooperative printing due to its ability to significantly increase the printing speed. It discusses current cooperative printing systems and proposes a new multi-arm configuration to address current limitations such as reduced cooperative printing area. The proposed configuration allows printing parts that are impossible to print or inefficiently printed by other configurations. Moreover, to improve efficiency and reduce printing time, new algorithms are proposed, including the Intermediate Point Method for collision avoidance. This method is three times more effective at preventing collisions compared to the current state-of-the-art algorithms and generates paths with lower travel durations. The proposed system was successfully tested in printing several single and multi-layer objects, showing a significant speed increase, surpassing the maximum printing time reduction reported in the literature.

Collision avoidance trajectory planning for a dual-robot system: using a modified APF method

AbstractDual-robot system has been widely applied to the field of handling and palletizing for its high efficiency and large workspace. It is one of the key problems of the trajectory planning to determine the collision avoidance method of the dual-robot system. In the present study, a collision avoidance trajectory planning method for the dual-robot system was proposed on the basis of a modified artificial potential field (APF) algorithm. The interference and collision criterion of the dual-robot system was given firstly, which was established based on the method of kinematic analysis in robotics. And then, in consideration of the problem of excessive virtual potential field force induced by using the traditional APF algorithm in the process of dual-robot trajectory planning, a modified APF algorithm was proposed. Finally, the modified APF algorithm was used for motion control of a dual-robot palletizing process, and the collision avoidance performance of the proposed collision avoidance algorithm was studied through a dual-robot palletizing simulation and experiment. The results have shown that with the proposed collision avoidance trajectory planning algorithm, the two robots in dual-robot system can maintain a safe distance at all times during palletizing process. Compared with the traditional APF and rapidly-exploring random tree (RRT) algorithm, the trajectory solution time of the modified APF algorithm is greatly reduced. And the modified APF algorithm’s convergence time is 14.2% shorter than that of the traditional APF algorithm.

Three-dimensional path planning and collision-free flight control for drone-assisted autonomous pollination systems

In this paper, the authors’ previous work regarding a conceptual drone-assisted autonomous pollination system (APS) is extended with regards to path planning and flight control. The APS Path Planning module is extended to optimize the path for missions requiring three-dimensional (3D) path planning, such as the pollination of almond trees. A new method of simplifying the 3D path planning problem by selecting cells or groups of flowers to visit is shown in this paper. This method is numerically demonstrated based on a simulated almond tree. The Flight Control module is extended to incorporate drag into a novel convex-optimization-based flight controller and a new method of collision avoidance called control sequence stitching (CSS). A linear drag model is integrated into the flight control formulation, which is validated through a simulated test flight. The concept of CSS is developed and explained as a method to generate seamless flight trajectories, while still reaping the benefits of convex optimization. This method can be used to generate collision-free trajectories and control commands rapidly for potential real-world APS missions.

Design and Field Test of Collision Avoidance Method With Prediction for USVs: A Deep Deterministic Policy Gradient Approach

Design and Field Test of Collision Avoidance Method With Prediction for USVs: A Deep Deterministic Policy Gradient Approach

OVERCOMING DOUBLE TAXATION: CURRENT STATE AND PROSPECTS

The problem of double taxation is currently a pressing issue for many countries and the international community in particular. This phenomenon has a negative impact on the economic development of countries, investment inflows, competitiveness in the international market and many other aspects. Therefore, the issue of overcoming double taxation is an urgent issue for many countries, including Ukraine, and international organisations. This is the reason for the relevance of this research. The purpose of this study is to analyse double taxation in terms of its generally accepted classification, its characteristics and current state; to determine the peculiarities of overcoming double taxation within the framework of application of double taxation avoidance methods; to analyse the prospects for activities aimed at overcoming double taxation and to characterise the achievements in multilateral tax cooperation. In order to achieve this goal, the following methods of scientific knowledge were used: general philosophical method, descriptive method, method of system analysis, synthesis, dialectical method, methods of deduction and induction. The conclusions drawn as a result of the study are scientifically significant and important for further research and improvement of the legal regulation of double taxation issues.

Research on Real Time Obstacle Avoidance Method for AUV Based on Combination of ViT-DPFN and MPC

Research on Real Time Obstacle Avoidance Method for AUV Based on Combination of ViT-DPFN and MPC