Presence Of Obstacles Research Articles

Guidance method of underwater vehicle for rugged seafloor observation in close proximity

AbstractObtaining detailed information about the ocean through seafloor optical imaging is crucial, yet poses significant challenges due to the high attenuation of light, which necessitates the camera to be positioned within several meters of the seafloor. This paper proposes a method for an autonomous underwater vehicle (AUV) to track the seafloor at a close range suitable for optical survey. Through the probabilistic processing of measurements from a mechanical scanning imaging sonar, the AUV can safely follow the seafloor, even in the presence of large obstacles or overhanging geometries. The method was implemented on the low‐cost AUV, HATTORI, and its effectiveness was confirmed by sea experiments around Nishinoshima island, an uninhabited volcanic island located about 1000 km south of Tokyo, Japan. Detailed images of the rugged seafloor were successfully captured under the challenging condition of strong currents.

Pedestrian lane formation with following–overtaking model and measurement of system order

Pedestrian self-organizing movement plays a significant role in evacuation studies and architectural design. Lane formation, a typical self-organizing phenomenon, helps pedestrian system to become more orderly, the majority of following behavior model and overtaking behavior model are imprecise and unrealistic compared with pedestrian movement in the real world. In this study, a pedestrian dynamic model considering detailed modelling of the following behavior and overtaking behavior is constructed, and a method of measuring the lane formation and pedestrian system order based on information entropy is proposed. Simulation and analysis demonstrate that the following and avoidance behaviors are important factors of lane formation. A high tendency of following results in good lane formation. Both non-selective following behavior and aggressive overtaking behavior cause the system order to decrease. The most orderly following strategy for a pedestrian is to overtake the former pedestrian whose speed is lower than approximately 70% of his own. The influence of the obstacle layout on pedestrian lane and egress efficiency is also studied with this model. The presence of a small obstacle does not obstruct the walking of pedestrians; in contrast, it may help to improve the egress efficiency by guiding the pedestrian flow and mitigating the reduction of pedestrian system orderliness.

Certified polyhedral decompositions of collision-free configuration space

Understanding the geometry of collision-free configuration space (C-free) in the presence of Cartesian-space obstacles is an essential ingredient for collision-free motion planning. While it is possible to check for collisions at a point using standard algorithms, to date no practical method exists for computing C-free regions with rigorous certificates due to the complexity of mapping Cartesian-space obstacles through the kinematics. In this work, we present the first to our knowledge rigorous method for approximately decomposing a rational parametrization of C-free into certified polyhedral regions. Our method, called C-Iris (C-space Iterative Regional Inflation by Semidefinite programming), generates large, convex polytopes in a rational parameterization of the configuration space which are rigorously certified to be collision-free. Such regions have been shown to be useful for both optimization-based and randomized motion planning. Based on convex optimization, our method works in arbitrary dimensions, only makes assumptions about the convexity of the obstacles in the 3D Cartesian space, and is fast enough to scale to realistic problems in manipulation. We demonstrate our algorithm’s ability to fill a non-trivial amount of collision-free C-space in several 2-DOF examples where the C-space can be visualized, as well as the scalability of our algorithm on a 7-DOF KUKA iiwa, a 6-DOF UR3e, and 12-DOF bimanual manipulators. An implementation of our algorithm is open-sourced in Drake. We furthermore provide examples of our algorithm in interactive Python notebooks.

OPTIMAL LONG-RANGE-WIDE-AREA-NETWORK PARAMETERS CONFIGURATION FOR INTERNET OF VEHICLES APPLICATIONS IN SUBURBAN ENVIRONMENTS

In this paper, the effect of Long-Range wireless technology parameters on signal propagation in suburban environments is investigated. Wireless propagation modeling provides information about the wireless channel and its impact on communication links. Received signal strength and coverage area are evaluated to determine signal path loss. The operating frequency of 433 MHz Long Range Wireless Area Network is utilized with different spreading factors, bandwidths, and code rates. Empirical propagation models are utilized to predict a mathematical model based on measured empirical signal strength in a suburban site in Baghdad City. The measured signal strength and signal-to-noise ratio values were obtained through drive tests in an Internet of Vehicles environment to design a network that could accurately report vehicle locations. The LoRa parameters affected the calculated path loss exponent, leading to various predictions in the network design. The path loss exponent exhibited instability due to the presence of obstacles and different long-range parameter settings. Path loss exponent deviation fluctuates due to bandwidth and spreading factor variations. Path loss exponent reduced at higher coding rates for more protection purposes. Packet ratio reception improved as the coding rate increased. To minimize the impact of the path loss on network design, an optimization policy was employed to determine the best parameters that resulted in the lowest path loss. The optimal path loss obtained at LoRa configuration parameters settings with spreading factor (7), bandwidth (500 kHz), and code rate (4/5).

PRM Path Smoothening by Circular Arc Fillet Method for Mobile Robot Navigation

The problem of motion planning and navigation for mobile robots in complex environments has been a central issue in robotics. Navigating these environments requires sophisticated algorithms that handle obstacles and provide smooth, efficient paths. The Probabilistic Roadmap (PRM) method is a widespread technique in robotics for constructing paths for mobile robot navigation. In this study, we propose a novel path-smoothing method using arc fillets for path planning, building on PRM's foundation in the presence of obstacles. Our method operates in two primary stages to improve path efficiency and quality. The first stage generates the shortest path between the initial and goal states in an obstacle-rich environment using PRM, constructing a straight-line, collision-free route. The second stage smooths corners caused by nodes with arc fillets, ensuring smooth turns and minimizing abrupt changes in direction, resulting in more natural and efficient robot motion. We conducted simulations and tests using various PRM features to evaluate the proposed method. The results indicate that the built route offers a smooth turning motion and quicker, more compact movement while evading obstacles. This study contributes to mobile robot navigation by offering a practical approach to improving pathway quality in challenging environments.

Obstacle Avoidance Robot using an Ulrasonic Sensor with Arduino Uno

The first function of obstacle avoidance robots is to detect the presence of obstacles. When you power on the system with the help of the ON/OFF switch, the Arduino microcontroller will read the data. When the ultrasonic sensor detects the presence of an obstacle in the process of moving forward, the robot will move backward. If the robot does not sense any obstacle, that is, if the distance between an obstacle and it is wide, it will then move forward again until it senses an obstacle before it stops. Two LEDs are used in the research, one indicating the robot is moving forward and the other showing if the robot is moving backward. The third LED shows if the battery is fully charged. C programming is used for Arduino board applications to develop the program for the whole system's operation. There is also a power source unit that is used to charge the batteries used in the system.

Simulation of Obstacle Avoidance Robots

The first function of the system is to detect the presence of obstacles. When the user activates the system using the power ON/OFF switch, the Arduino microcontroller will read the data. When the ultrasonic sensor detects the presence of an obstacle in the process of moving forward, the robot will move backward. If the robot does not sense any obstacle, that is, if the distance between an obstacle and it is wide, it will then move forward again until it senses an obstacle before it stops. C programming is used for Arduino board applications to develop the program for the whole system's operation. There are three light-emitting diodes; the first one shows the amount of charge in the batteries, while the remaining two show that if the robot is moving forward, one of the two LEDs will be on, and if it is moving backward, one of the LEDs will also be on. There is also a power source unit that is used to charge the batteries used in the system.

An efficient determination of field distributions in E-plane dielectric loaded waveguides

ABSTRACT This paper proposes a new, fast, and efficient method for determining the electromagnetic field distribution in two-port E-plane dielectric-loaded uniform rectangular waveguides. The analysis region is divided into individual blocks in the absence and presence of dielectric obstacles. The non-zero electric and magnetic field components are constructed throughout the system via the proposed method by utilizing the generalized scattering matrix method between blocks for unimodal or multimodal excitation. The resulting field distributions are compared to those obtained from commercial software, with very close agreement achieved, but with a significantly reduced computational time for the proposed method. The method is applicable in a straightforward manner and has been tested on both a filter device with relatively complex geometry and a disjoint system with a modal coupling challenge between its elements. The field components' accuracy is also tested by calculating the Poynting vector along the system. Additionally, this approach provides the global scattering parameters at the physical ports as a co-product. The proposed method has the potential to be applied to various two-port networks by using the proposed method according to the considered problem.

3D traversability analysis and path planning based on mechanical effort for UGVs in forest environments

Autonomous navigation in rough and dynamic 3D environments is a major challenge for modern robotics. This paper presents a novel traversability analysis and path planning technique that processes 3D point cloud maps to compute terrain gradient information and detect the presence of obstacles to generate efficient paths. These avoid unnecessary slope changes when more conservative paths are available, potentially promoting fuel economy, reducing the wear on the equipment and the associated risks. The proposed approach is shown to outperform existing techniques both in 3D simulation scenarios as well as in a real forest dataset, in which it also generates paths that are comparable to the ones drawn by humans with different backgrounds and expertise levels.

The impact of people-signage interaction on way-finding evacuation behaviour

A Virtual Reality (VR) experiment with 60 participants was carried out to investigate the effect of signage on the compliance with its indicated direction in case of evacuation. Participants experienced a VR underground square scenario including different signage configurations. Variables linked to the signage placement/type were investigated, namely (1) the installation position, i.e., proximity to the indicated route, angle of interaction, and (2) the type of signage, i.e., signage on the floor, one-face signage on the ceiling, four-faced signage on the ceiling. Results show that the angle of interaction affects the evacuees’ chosen direction. Signage on the floor may lead to higher compliance to the indicated direction in presence of obstacles. Four-faced signage may lead to uncertainty since the viewer may see two faces displaying two different directions on the sign.

INVESTIGATION OF THE EFFECTIVENESS FOR PROTECTIVE SCREENS OF VARIOUS FORMS ON AIR POLLUTION REDUCTION

Problem statement. The task of evaluating the effectiveness of the use of protective screens of different geometric shapes to reduce the level of air pollution is considered. The data on the screen allow you to change the aerodynamics of the air flow and redirect the movement of polluted air away from the work areas in the other direction. The purpose of the article – study of the effectiveness of the use of protective screens of different geometric shapes to reduce the level of pollution, creation of a three-dimensional numerical model for the analysis of the effectiveness of the use of protective screens. Methodology. The method of physical experiment in laboratory conditions is used to analyze the effectiveness of screens of different geometric shapes. Three-dimensional equations of aerodynamics and mass transfer are used for mathematical modeling of impurity propagation in the presence of screens. The developed numerical model makes it possible to take into account the air flow velocity profile, atmospheric diffusion, the emission intensity of the impurity, the rate of gravitational sedimentation of the impurity in the air. For the numerical integration of the modeling equations of aerodynamics and mass transfer, finite-difference splitting schemes are used. Scientific novelty. Data on the effectiveness of the use of four protective screens, which differ in geometric shape, were obtained experimentally. Experimental data make it possible to carry out an initial assessment of the impact of various screens on reducing the level of pollution in working areas. A fast-calculating 3D numerical model was developed for solving problems of aerodynamics and mass transfer in relation to the problem of evaluating the effectiveness of the use of screens located in areas where atmospheric air pollution occurs. Practical significance. Experimental data make it possible to justify the choice of a protective screen near the highway or another area on the industrial site where the impurity emission takes place. A computer code was created on the basis of the developed mathematical model, which makes it possible to predict the intensity of air pollution in the presence of obstacles that change the aerodynamics and the direction of transport of impurities in the atmosphere. Conclusions. The results of the physical experiment allow us to imagine the regularities of the formation of areas of pollution near protective screens of different geometric shapes, the developed mathematical model allows us to estimate air pollution in areas where there are obstacles in the way of the movement of impurities. The results of physical and computational experiments are presented.

Sound Pressure Field Reconstruction for Airborne Ultrasound Tactile Display Encountering Obstacles.

Airborne ultrasound tactile display (AUTD) is used to provide non-contact tactile sensations with specific foci sound fields through the optimization of transducer phases. However, most existing optimization approaches are not directly applicable in case of an inhomogeneous medium, such as in the presence of obstacles between the AUTD and objective sound field. Certain methods can perform optimizations by considering the sound-scattering surfaces of the obstacles to compute the transmission matrix, which requires several complex measurements. This study proposed two methods to reconstruct the sound field under an inhomogeneous medium, wherein the need to calculate the impact of the obstacles was eliminated. The two methods are Bayesian optimization and greedy algorithm with brute-force search. Further, the process of the foci field generation was assumed as a black box. The proposed methods require only the pressure intensity at the control point generated by the input phases, discarding the need for transmission matrix in the presence of obstacles. Moreover, these methods offer the advantage of optimization of the phases in the presence of obstacles. This study explains the working of proposed methods in different forms of foci fields encountering obstacles.

Opportunities and Challenges of LoRa 2.4 GHz

Internet of Things (IoT) technologies are increasingly used in our daily life. Among these technologies, LoRa is widely used for low power IoT data collection in wide areas. LoRa typically operates in sub-GHz bands which are region-specific, and thus has limited world-wide applications. The version of LoRa developed for the 2.4 GHz ISM band has spurred recent interest in the scientific community, as it enables the use of worldwide frequency channels. However, it requires the coexistence with numerous concurrent technologies within this 2.4 GHz band, and an evolution of the MAC and networking protocols for utilizing LoRaWAN connectivity. In this paper, we make the first experimental comparison between LoRa sub-GHz and LoRa 2.4 GHz in both indoor and outdoor scenarios. We show that LoRa 2.4 GHz can have a communication range of more than 2 km outdoor, and it can achieve a packet delivery rate of at least 0.98 for a distance of up to 39 meters indoor with the presence of obstacles. We also make an extensive discussion on the researches challenges that need to be addressed in order to fully take advantage of this new technology.

Variation in the Spectral Content of UHF PD Signals Due to the Presence of Obstacles in the Measurement Environment

Variation in the Spectral Content of UHF PD Signals Due to the Presence of Obstacles in the Measurement Environment

Deep Learning Based Obstacle Awareness from Airborne Optical Sensors

Aviation statistics identify collision with terrain and obstacles as a leading cause of helicopter accidents. Assisting helicopter pilots in detecting the presence of obstacles can greatly mitigate the risk of collisions. However, only a limited number of helicopters in operation have an installed helicopter terrain awareness and warning system (HTAWS), while the cost of active obstacle warning systems remains prohibitive for many civil operators. In this work, we apply machine learning to automate obstacle detection and classification in combination with commercially available airborne optical sensors. While numerous techniques for learning-based object detection have been published in the literature, many of them are data and computation intensive. Our approach seeks to balance the detection and classification accuracy of the method with the size of the training data required and the runtime. Specifically, our approach combines the invariant feature extraction ability of pretrained deep convolutional neural networks (CNNs) and the high-speed training and classification ability of a novel, proprietary frequency-domain support vector machine (SVM) method. We describe our experimental setup comprising the CNN + SVM model and datasets of predefined classes of obstacles—pylons, chimneys, antennas, TV towers, wind turbines, helicopters—synthesized from prerecorded airborne video sequences of low-altitude helicopter flight. We analyze the detection performance using average precision, average recall, and runtime performance metrics on representative test data. Finally, we present a simple architecture for real-time, onboard implementation and discuss the obstacle detection performance of recently concluded flight tests.

Effective Physical Education in Inclusive Classes from the Point of View of Physical Culture Teachers

Topicality. Today, the New Ukrainian School was introduced, and with it, inclusive education. The importance of providing high-quality educational services for schoolchildren is growing. Scientific research devoted to the fundamental aspects of inclusive physical education appears to be insufficient. The Purpose of the work is to establish a rating of factors that prevent the effective organization of the physical education process in inclusive classes of general secondary education institutions; to find out which approaches are important for physical education in inclusive classrooms to be effective. Methods. A survey of physical education teachers (n=73) was conducted. Consistency of respondents’ answers was determined using Kendall’s concordance coefficient. The Results. Among the main problems are the imperfection of the legislative framework, the lack of proper content of the program material, limited access to methodical support for inclusive physical education lessons. It is also necessary to solve the problems associated with ignoring the motivation of students and the low level of children’s physical condition. Problems also arise as a result of the mismatch of human resources with modern needs. The lack of objective information about the health and physical development of schoolchildren, an imperfect system of medical and pedagogical control, in particular, incorrect criteria for dividing students of inclusive classes into groups make it difficult to form homogeneous groups in an inclusive class. Teachers need support from specialists in the field of medicine and rehabilitation. Conclusions. The survey of teachers confirms the presence of numerous obstacles in the physical education of students in inclusive classes. The introduction of the position of a rehabilitation teacher can significantly increase the effectiveness of physical education lessons in inclusive classes. In order for the physical education lesson in inclusive classes to be effective, it is important to divide the class into homogeneous groups that are small in number of participants depending on the level of children’s abilities and for each of them to adapt the means and differentiate the volume and intensity of the load. Modification of equipment for students with special educational needs is rational.

Distributed Control for Multi-Robot Interactive Swarming Using Voronoi Partioning

The problem of safe navigation of a human-multi-robot system is addressed in this paper. More precisely, we propose a novel distributed algorithm to control a swarm of unmanned ground robots interacting with human operators in presence of obstacles. Contrary to many existing algorithms that consider formation control, the proposed approach results in non-rigid motion for the swarm, which more easily enables interactions with human operators and navigation in cluttered environments. Each vehicle calculates distributively and dynamically its own safety zone in which it generates a reference point to be tracked. The algorithm relies on purely geometric reasoning through the use of Voronoi partitioning and collision cones, which allows to naturally account for inter-robot, human-robot and robot-obstacle interactions. Different interaction modes have been defined from this common basis to address the following practical problems: autonomous waypoint navigation, velocity-guided motion, and follow a localized operator. The effectiveness of the algorithm is illustrated by outdoor and indoor field experiments.

Mutual validation of remote hydraulic estimates and flow model simulations using UAV-borne LiDAR and deep learning-based imaging techniques

Hydraulic modeling plays a pivotal role in various river-related applications, but acquiring precise datasets can be challenging due to complex environments and limited availability of field data. To address these challenges, remote sensing approaches have shown promise, but their widespread scientific use requires validation. This study investigates the utilization of an uncrewed aerial vehicle (UAV)-integrated topo-bathymetric green LiDAR system (GLS) combined with deep learning-based space-time image velocimetry (DL-STIV) techniques to remotely analyze hydraulic properties in the lower Asahi River, Japan. The research compares streamflow measurements with flow model simulations at four transects within a 1.2 km gravel bed channel with vegetation. The results demonstrate that the DL-STIV technique provides reliable velocity estimates, with root-mean-square errors ranging from 0.014 to 0.247 m/s. When using a typical velocity conversion factor of 0.85, the DL-STIV method aligns well with model predictions, yielding coefficient of determination values between 0.850 and 0.959. However, the choice of conversion index (ranging from 0.75 to 0.95) significantly affects accuracy. The study also reveals that remotely estimated discharges are reasonably consistent with model estimates, with errors ranging from 0.026 to 11.124%. However, accuracy is influenced by factors such as the presence of obstacles, uncertainties in remotely sensed water depths, and the choice of reference values. In conclusion, this research demonstrates the suitability and potential of GLS and DL-STIV for remotely analyzing hydraulic properties in rivers. The study also points to the importance of considering potential variations and uncertainties when adopting these techniques for flow modeling and validation purposes.

Autonomous medical needle steering in vivo.

The use of needles to access sites within organs is fundamental to many interventional medical procedures both for diagnosis and treatment. Safely and accurately navigating a needle through living tissue to a target is currently often challenging or infeasible because of the presence of anatomical obstacles, high levels of uncertainty, and natural tissue motion. Medical robots capable of automating needle-based procedures have the potential to overcome these challenges and enable enhanced patient care and safety. However, autonomous navigation of a needle around obstacles to a predefined target in vivo has not been shown. Here, we introduce a medical robot that autonomously navigates a needle through living tissue around anatomical obstacles to a target in vivo. Our system leverages a laser-patterned highly flexible steerable needle capable of maneuvering along curvilinear trajectories. The autonomous robot accounts for anatomical obstacles, uncertainty in tissue/needle interaction, and respiratory motion using replanning, control, and safe insertion time windows. We applied the system to lung biopsy, which is critical for diagnosing lung cancer, the leading cause of cancer-related deaths in the United States. We demonstrated successful performance of our system in multiple in vivo porcine studies achieving targeting errors less than the radius of clinically relevant lung nodules. We also demonstrated that our approach offers greater accuracy compared with a standard manual bronchoscopy technique. Our results show the feasibility and advantage of deploying autonomous steerable needle robots in living tissue and how these systems can extend the current capabilities of physicians to further improve patient care.

REVISITING WAVE PROPAGATION UNDER AIR FLOW IN COASTAL AREAS

The interaction between ocean waves and winds can be separated into two main analyses. A first interaction considers the wind as the primary wave generator. The mechanism through which wind exerts stresses to the water surface that combined with the gravity forces produce the surface oscillatory flow known as waves, is relatively well documented theoretically (Blennerhassett 1980), experimentally (Plate et al. 1969) and numerically (Liu et al. 2016). On the other hand, as waves travel to the coast, winds stop being the generating force and turn into an energy source travelling along with the waves. In places close to the shore, winds can be directed with or against the wave propagation. It is straightforward that wave properties close to the shore are modified under different wind conditions (Xie 2017). Numerical and experimental studies on wave-wind interaction near the coast and in presence of obstacles exist but are still scarce (Medina 2001). The present research is an experimental study of the perturbation produced by an air flow over waves in shallow waters and interacting with sloped obstacles. Well-known phenomena such as wave braking, steepening and run-up are revisited under wave-wind conditions.