Automatic Navigation System Research Articles

A review of research about automatic navigation system of mobile robots based on ROS

A review of research about automatic navigation system of mobile robots based on ROS

AM-UNet: Field Ridge Segmentation of Paddy Field Images Based on an Improved MultiResUNet Network

In order to solve the problem of image boundary segmentation caused by the irregularity of paddy fields in southern China, a high-precision segmentation method based on the improved MultiResUNet model for paddy field mapping is proposed, combining the characteristics of paddy field scenes. We introduce the attention gate (AG) mechanism at the end of the encoder–decoder skip connections in the MultiResUNet model to generate the weights and highlight the response of the field ridge area, add an atrous spatial pyramid pooling (ASPP) module after the end of the encoder down-sampling, use an appropriate combination of expansion rates to improve the identification of small-scale edge details, use 1 × 1 convolution to improve the range of the sensory field after bilinear interpolation to increase the segmentation accuracy, and, thus, construct the AM-UNet paddy field ridge segmentation model. The experimental results show that the IoU, precision, and F1 value of the AM-UNet model are 88.74%, 93.45%, and 93.95%, respectively, and that inference time for a single image is 168ms, enabling accurate and real-time segmentation of field ridges in a complex paddy field environment. Thus, the AM-UNet model can provide technical support for the development of vision-based automatic navigation systems for agricultural machines.

The bearings and distances isolines combinations of the navigational landmarks pair for the vessel fixed position determination

The issues of applying basic navigation parameters (bearing and distance), and their isolines traditionally used in navigation practice in coastal waters are studied in the paper. A new distinctive feature is the use of isolines combinations (three distance arcs, two isoazimuths, a hyperbola and an ellipse) based on measured bearings and distances to the pair of landmarks to obtain the vessel fixed positions with high precision. The traditional navigation methods (the theory of isolines, the generalized method of lines position, the method of least squares) are involved as a mathematical framework. The mathematical argumentation and the isolines characteristics of bearings and distances, their combinations (difference and sum of distances, difference of bearings) are given. The solutions of the surplus equations of the lines position under random error influence by the least squares method and the accuracy assessment of the vessel fix position by the radial error including the reduced variant to compensate the systematic errors are suggested. The principal points of the research are supported by the graphic interpretation, and the given expressions are adjusted to the practical application and navigation systems software development. The computer simulation that shows the radial error of the fixed position by seven position lines is at least two times less than by any pair of position lines has been carried out. The formalization of the proposed methods in the automatic navigation systems or in autonomous ship control systems will enable the navigator on board or at operating the vessel remotely to solve the problems of the navigation information processing in coastal and congested waters on a new level.

Design of an Automatic Navigation and Operation System for a Crawler-Based Orchard Sprayer Using GNSS Positioning

In order to enhance the efficiency of agricultural machinery in orchard rows and minimize harm to personnel caused by pesticide spraying, this study developed a GNSS-based (Global Navigation Satellite System) automatic navigation driving system for tracked orchard sprayers. The tracked sprayer was used as a platform for this research. We constructed both a crawler hydraulic platform and spraying working parts based on orchard operation requirements. Additionally, we designed the hydraulic and electrical sub-control process of the crawler platform. By utilizing the motion model of the tracked mobile platform, we designed a linear path tracking control method using position deviation and heading deviation as state quantities. This allows the research platform to automatically initiate and terminate, travel in a straight line between rows, and complete spraying operations. Experimental verification confirmed that the tracked sprayer designed in this study successfully achieves automatic driving. The best automatic driving performance is achieved at a speed of 1.0 m/s. When the sprayer’s speed is 1.2 m/s, the maximum value of the straight-line path tracking accuracy of the platform’s automatic driving is better than 5.6 cm, with a standard deviation of 2.8 cm. This system effectively meets the requirements of automatic operation for an automatic spraying machine, thereby establishing a foundation for the implementation of automatic spraying operations in orchards.

Intraoperative artificial intelligence system identifying liver vessels in laparoscopic liver resection: a retrospective experimental study.

The precise recognition of liver vessels during liver parenchymal dissection is the crucial technique for laparoscopic liver resection (LLR). This retrospective feasibility study aimed to develop artificial intelligence (AI) models to recognize liver vessels in LLR, and to evaluate their accuracy and real-time performance. Images from LLR videos were extracted, and the hepatic veins and Glissonean pedicles were labeled separately. Two AI models were developed to recognize liver vessels: the "2-class model" which recognized both hepatic veins and Glissonean pedicles as equivalent vessels and distinguished them from the background class, and the "3-class model" which recognized them all separately. The Feature Pyramid Network was used as a neural network architecture for both models in their semantic segmentation tasks. The models were evaluated using fivefold cross-validation tests, and the Dice coefficient (DC) was used as an evaluation metric. Ten gastroenterological surgeons also evaluated the models qualitatively through rubric. In total, 2421 frames from 48 video clips were extracted. The mean DC value of the 2-class model was 0.789, with a processing speed of 0.094s. The mean DC values for the hepatic vein and the Glissonean pedicle in the 3-class model were 0.631 and 0.482, respectively. The average processing time for the 3-class model was 0.097s. Qualitative evaluation by surgeons revealed that false-negative and false-positive ratings in the 2-class model averaged 4.40 and 3.46, respectively, on a five-point scale, while the false-negative, false-positive, and vessel differentiation ratings in the 3-class model averaged 4.36, 3.44, and 3.28, respectively, on a five-point scale. We successfully developed deep-learning models that recognize liver vessels in LLR with high accuracy and sufficient processing speed. These findings suggest the potential of a new real-time automated navigation system for LLR.

Interfacial Engineering of Quantum Dots–Metal–Organic Framework Composite Toward Efficient Charge Transport for a Short‐Wave Infrared Photodetector

AbstractShort‐wave infrared (SWIR) quantum dot (QD)‐converted photodetectors are one of the promising devices used in artificial intelligence and automatic navigation systems. However, compared to semi‐conductor‐type photodetectors, they suffer from poor chemical stability and weak electronic conductivity. In this study, a PbS QD and conductive metal–organic framework (MOF) hybrid composite is designed with SWIR detection capability. The Fourier‐transform infrared spectroscopy confirms the surface modification of PbS QDs with MOF. X‐ray absorption near‐edge structures spectra reveal the chemical bonding between MOF and PbS QDs. Furthermore, 2D grazing‐incidence small‐ and wide‐angle X‐ray scattering is utilized to unveil the particle stacking and the preferred orientation of the PbS@MOF thin film. By integrating the PbS@MOF thin film directly on top of the graphene field effect transistor (FET) device, the chemical stability and photoelectric properties of graphene FET are enhanced, and these are investigated using a focus ion beam with a high‐resolution transmission electron microscope. This study offers a strategy to simultaneously improve the chemical stability and the photoelectronic properties of the nanomaterials as well as contribute to the advancement of a QD‐converted SWIR photodetector.

Application of fuzzy controllers in automatic ship motion control systems

Automatic ship heading control is a part of the automatic navigation system. It is charged with the task of maintaining the actual ship’s course angle or actual ship’s course without human intervention in accordance with the set course or setting parameter and maintaining this condition under the effect of disturbing influences. Thus, the corrective influence on deviations from a course can be rendered by the position of a rudder or controlling influence that leads to the rotary movement of a vessel around a vertical axis that represents a problem, which can be solved with the use of fuzzy logic. In this paper, we propose to consider the estimation of the efficiency of fuzzy controllers in systems of automatic control of ship movement, obtained by analysis of a method of the formalized record of a logic conclusion and structure of the fuzzy controller. The realization of this allows to carry out effective stabilization of a course angle of a vessel taking into account existing restrictions.

Planning and control of the ship curvilinear route

The possibility of applying the traditional navigation parameters used in pilotage (bearing and distance), as well as their sum and difference for planning and controlling the ship curvilinear route in coastal waters is being investigated. Mathematical apparatus is based on the classical navigation methods such as the theory of isolines, the lines of position, the principles of route planning, as well as the approximation of the curvilinear route. The mathematical justification of the circle arcs, ellipse and hyperbola used as the approximation lines of both the ship curvilinear route and the control isolines is given. The methods for estimating the vessel approaching to the point of the beginning and end of the turn and for controlling the ship movement along the planned path by measuring the navigational parameters are proposed. The problems of the physical and mathematical feasibility of the route arising at the junction points of the straight and curvilinear parts of the ship route are recommended to be resolved on the principles of transition curves (clothoids), considering the maneuvering characteristics of the vessel. The main theses of the research are supported by the graphical interpretation while the given expressions are ready for practical application. The formalization of the proposed methods in both automatic navigation systems and autonomous ship control systems will allow the navigator on the bases of the configuration of the relative position of landmarks and the ship curvilinear route to solve the problems of processing relevant navigation information in coastal and congested waters more efficiently in conjunction with the traditional pilotage methods, which is especially important for advanced autonomous navigation.

Spline standard of mapped informativeness of correlation-extreme navigation as the potential of cybernetic situational awareness

A hypothesis about the possibility of using a spline standard of mapped informativeness of correlation-extreme navigation as a potential for cybernetic awareness is put forward. The expediency of understanding cybernetic awareness as an ontological engineering of the geometric implementation of a spline fragment of mapping to ensure the principle of alternative positioning is revealed. The forecast of the achievability of the effect of the vessel location predictability in the local environment of the satellite signals incapacity in the practical realization of the potential of situational awareness is made. The possibility of conceptual resistance of the developed algorithms of malicious virtual interference due to the unique composition of spline functions in assessing the vulnerability of the bridge onboard computers to a cybernetic threat is substantiated. Attention is focused on the fundamental impossibility of distorting the spline standard of informativeness to disrupt the classical process of linking the measured exposure of the navigation field to the reference one to ensure autonomous positioning of moving objects in any hacker attacks on the target mathematical asset. The main reason for the stability of approximation constructions, which lies in the piecewise architecture of the spline, when local violations of mathematical composition do not affect the overall task of forming a realistic navigation isosurface as a graphical structure of semantic modeling, is revealed. The proposals of effective information processing as attributes of cybernetic awareness are tested on the example of computer visualization of measuring fields of bathymetry and maps of magnetic anomalies in the form of fragments of threedimensional spreading of the planetary magnetic field. The developed package of application programs is adapted to synthesize a spline standard of mapped informativeness in the cybernetic awareness paradigm as an intellectual support for decision-making by a navigator in order to reduce his psychological cognitive load. It is proposed to use the potential of situational awareness as a mathematical support for an automated navigation system with artificial intelligence within the framework of the concept of unmanned navigation in strategic accordance with the A-Navigation project. The fundamental importance of a positive assessment of cybernetic awareness in promoting the practical use of autonomous marine surface vessels in modern navigation practice is determined.

Agricultural machinery photoelectric automatic navigation control system based on back propagation neural network

So as to study the influence of speed factors on the stability of tractor automatic navigation system, combined with neural network control theory, the author proposed a dual-objective joint sliding mode control method based on lateral position deviation and heading angle deviation, using back propagation neural network to establish two-wheel tractor-path dynamics model and straight-line path tracking deviation model, the overall system simulation was carried out by using Matlab/Simulink, and the reliability of the control method was verified. The experimental results showed: when the tractor was tracked with the automatic control of linear path under the condition of the variable speed, the maximum deviation of the lateral position deviation was 12.7cm, and the average absolute deviation was kept within 4.88cm; the maximum deviation of the heading angle deviation was 5°, and the average absolute deviation was kept within 2°; the maximum value of the actual rotation angle was 3.13°, and the standard deviation of the fluctuation was within 0.84°. Under the condition of constant speed and variable speed, using the joint sliding mode control method designed by the author, the dual-objective joint control of lateral position deviation and heading angle deviation could be realized, the controlled overshoot was small, the controlled deviation was small after reaching a stable state, and the adaptability to speed factors was strong, which basically could meet the accuracy requirements of farmland operations.

Design Of Multi Sensor Quadcopter Navigation Data Acquisition For Early Fire Detection and Treatment

Recently, forest and land fires have become an event that has become a concern for the national and international community. This research creates a quadcopter as a tool for detecting forest and land fires. This system is an alternative tool for detecting forest and land fires that already exist. The advantage of this quadcopter is that it can collect data before the fire, during the fire, and after the fire. This quadcopter is designed and realized the developm­­­­­ent of an automatic navigation system for unmanned aircraft. This system is controlled by a microcontroller that processes IMU (Inertial Measurement Unit) sensor data in which there is a gyroscope and accelerometer, GPS, and magnetometer so that it can fly automatically. The purpose of this study is to acquire data on the navigation sensors used in the unmanned aerial vehicle (UAV) design, then the data from the navigation sensors will be combined using complement and median filters as position control input for the quadcopter. Based on this research, processing from sensor readings to sensor integration is able to produce better data, where the quadcopter's angle of view has an error percentage of 1.10° and 0.68°. This value is smaller than the percentage error of the magnetometer sensor alone or the IMU sensor alone which results in an error percentage of 1.18° and 0.76°.

Performance-Driven Metamorphic Testing of Cyber-Physical Systems

<i>Cyber-physical systems</i> (CPSs) are a new generation of systems, which integrate software with physical processes. The increasing complexity of these systems, combined with the uncertainty in their interactions with the physical world, makes the definition of effective test oracles especially challenging, facing the well-known <i>test oracle problem</i>. Metamorphic testing has shown great potential to alleviate the test oracle problem by exploiting the relations among the inputs and outputs of different executions of the system, so-called <i>metamorphic relations</i> (MRs). In this article, we propose an MR pattern called PV for the identification of performance-driven MRs, and we show its applicability in two CPSs from different domains, which are automated navigation systems and elevator control systems. For the evaluation, we assessed the effectiveness of this approach for detecting failures in an open-source simulation-based autonomous navigation system, as well as in an industrial case study from the elevation domain. We derive concrete MRs based on the PV pattern for both case studies, and we evaluate their effectiveness with seeded faults. Results show that the approach is effective at detecting over 88&#x0025; of the seeded faults, while keeping the ratio of FPs at 4&#x0025; or lower.

EYE-DIRECTION-BASED SAFETY NAVIGATION SYSTEM FOR ELDERLY AND PHYSICALLY CHALLENGED PERSONS

This research paper includes the eye-direction-based safety automated navigation system that was implemented for the elderly and physically challenged people. The purpose of this navigation system is to avoid the assistance required for physically challenged people. This system, which controls the motorised wheelchair navigation, depends on pupil detection. The sequential images were captured via Bluetooth specs glass using an image processing technique. The system navigates in the directions specified by the user, such as "move to the left," "move to the right," "move forward," and "stop." Additionally, a sensor is fixed in front of the wheelchair to detect objects and avoid faulty navigation. A centralised wireless detector device is also available in a wheelchair for emergency purposes. A Raspberry Pi Model B is a high-speed detection kit controlled by the whole system.

Design and Test of an Automatic Navigation Fruit-Picking Platform

With the development in agricultural mechanization and information technology, orchard agricultural machinery is also constantly pursuing the goal of intelligence and efficiency. Fruit picking is the most labor-intensive part of the orchard harvesting process. In order to resolve the problems of high labor intensity, low picking efficiency, and labor shortage when harvesting dwarf high-density orchards, an automatic navigation fruit-picking platform with voice control was developed in the present study. First, the platform utilized a voice-controlled high-level extendable working platform and a fruit-box-lifting device to adapt to varying orchard planting row spacing and enable convenient fruit box loading and unloading. Second, an automatic navigation system, which employed China’s Beidou navigation satellite system to acquire positional data and the Stanley algorithm for path-tracking control, was implemented. Third, the fruit-picking platform with automatic navigation system was fabricated and assembled, its outer wheel steering was measured to have a maximum angle of 30.3° and an average minimum turning radius of 4.5 m, meeting the turning radius requirements under orchard conditions. Finally, automatic navigation tests of the developed platform were performed in the orchard conditions. The results indicated that the platform could maintain a straight-line path with a maximum lateral deviation of 101.5 mm and a maximum absolute average deviation of 44.1 mm at 0.4 m/s. Under the U-shaped paths, the measured maximum lateral deviation was 148.6 mm and the maximum absolute average deviation was 57.2 mm. The navigation accuracy was sufficient to meet the requirements for the harvesting platform’s routine operation in the orchards.

Brain Controlled Car for Disabled Using Artificial Intelligence

This paper considers the development of a brain driven car, which would be of great help to the physically disabled people. Since these cars will rely only on what the individual is thinking they will hence not require any physical movement on the part of the individual. The car integrates signals from a variety of sensors like video, weather monitor, anti-collision etc. it also has an automatic navigation system in case of emergency. The car works on the asynchronous mechanism of artificial intelligence. It’s a great advance of technology which will make the disabled, abled. In the 40s and 50s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton and the Ratio Club in England. Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them. A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.

RPLiDAR-Based Mapping in Development of a Health Service Assisting Robot in COVID-19 Pandemic

Due to the Covid-19 pandemic, robots with various functions in the health sector are growing, one of which is autonomous robots capable of supporting logistics, drug and food delivery, and monitoring the environment. In this study, a map-based indoor navigation system was developed on health service assisting robot based on LiDAR and Robot Operating System (ROS) platform. The robot with the SLAM GMapping algorithm was succeeded to perform mapping with an accuracy of 95.983%. Then the robot with an automatic navigation system using the AMCL Particle Filter algorithm for localization was succeeded to perform localization with an error of 1.3377 on the x-axis and 1.2109 on the y-axis and 45,72570 for orientation on the z-axis. And succeeded to do trajectory tracking using the move_base package for path planning with an error of 1.6477 on the x-axis and 0.4498 on the y-axis when moving towards the target coordinates.

Risk-Averse Equilibria for Vehicle Navigation in Stochastic Congestion Games

The fast-growing market of autonomous vehicles, unmanned aerial vehicles, and fleets in general necessitates the design of smart and automatic navigation systems considering the stochastic latency along different paths in the traffic network. The longstanding shortest path problem in a deterministic network, whose counterpart in a congestion game setting is Wardrop equilibrium, has been studied extensively, but it is well known that finding the notion of an optimal path is challenging in a traffic network with stochastic arc delays. In this work, we propose three classes of risk-averse equilibria for an atomic stochastic congestion game in its general form where the arc delay distributions are load dependent and not necessarily independent of each other. The three classes are risk-averse equilibrium (RAE), mean-variance equilibrium (MVE), and conditional value at risk level <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> equilibrium ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{CVaR}_{\alpha}\text{E}$ </tex-math></inline-formula> ) whose notions of risk-averse best responses are based on maximizing the probability of taking the shortest path, minimizing a linear combination of mean and variance of path delay, and minimizing the expected delay at a specified risky quantile of the delay distributions, respectively. We prove that for any finite stochastic atomic congestion game, the risk-averse, mean-variance, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{CVaR}_{\alpha}$ </tex-math></inline-formula> equilibria exist. We show that for risk-averse travelers, the Braess paradox may not occur to the extent presented originally since players do not necessarily travel along the shortest path in expectation, but they take the uncertainty of travel time into consideration as well. We show through some examples that the price of anarchy can be improved when players are risk-averse and travel according to one of the three classes of risk-averse equilibria rather than the Wardrop equilibrium.

Finding Risk-Expenses Pareto-Optimal Routes in Ice-Covered Waters

Multi-objective optimization of a vessel route is considered of key importance when creating automatic navigation systems to ensure independent navigation in ice conditions. This is explained by the need to take into account not only the time or fuel expenditures on the route but also the risks. Previously, only a few models for navigation in ice used the multi-objective approach when finding the set of Pareto-optimal solutions. This paper suggests the multi-objective model of ship routing optimization with usage of the ice chart and ship parameters. Risks for a vessel are related to values of ice thickness and ice concentration in regions to travel through, which are specified by the ice chart. In the model, we use the extended version of the wave algorithm to find a set of routes, from which we select solutions of the Pareto-front for the multi-objective problem. The model uses objective functions of route length, maximum ice thickness, and maximum ice concentration. In addition, the travel time calculations are used in the model. Kaj Riska’s model of ship performance in ice is used for calculating travel time; the speed of a vessel is evaluated in each of the graph edges. The computational example provided in the paper is based on the particular ice chart of the Gulf of Finland. The developed method can be easily implemented for assisting a particular ship in independent ice navigation with the presence of a relevant ice chart.

Первый опыт навигационной лазерной коагуляции сетчатки в лечении активной ретинопатии недоношенных

Purpose is to demonstrate the first experience of the automated navigation system “Navilas” using in the treatment of active stages of retinopathy of prematurity (ROP) in the Kaluga branch of “Eye Microsurgery” complex. Material and methods. Transpupillary retinal laser coagulation (RLC) using the “Navilas 577s” navigation system (OD-OS, Germany) was performed in 5 premature infants with an unfavorable type of stages 2nd and 3rd of active ROP. The postconceptual age (PCA) at the time of treatment was 34–37 weeks. Body weight at birth – from 900 to 1900 g, gestation age – 27–33 weeks. Results. The “Eye tracking” function ensured the absolute accuracy of the laser spots, as well as the uniformity and safety of their application during the automated navigation RLC. After 1 month, the formation of chorioretinal atrophy zone with heterogeneous pigmentation was noted in all patients at the site of the RLC. The growth of retinal vessels into the avascular retina in the direction of ora serrata was observed. Conclusion. The first experience has shown that RLC of the avascular retina on the automated navigation system “Navilas” is safe, precision, metered, topographically oriented, which in the future will allow to standardize the technique of laser treatment for patients with ROP active stages. Keywords: retinopathy of prematurity, unfavorable type, navigation retinal laser coagulation.

Autonomous Agriculture Robot for Monitoring Plant using Internet of Things

Agriculture robot refers to the implementation of modern technology that combines robotics and automation to overcome deficiencies of the traditional agricultural method by automating processes to dramatically increase efficiency. The robot is designed with a fully automated navigation system using line following algorithm with added features to monitor and capture the image of the plant in real-time situations. This project aims to develop a system to monitor the conditions of crops and designing a logic control for line following navigation within the boundaries of modern agriculture. The system will be realized following the process chain starting from the mapping the input from sensors to control the speed and direction of the motor. The user will be able to monitor the plant condition from the image captured through internet of things-based communication between the robot and Blynk application.