Autonomous Object Research Articles

Challenges and Opportunities for Autonomous Micro-UAVs in Precision Agriculture

Mobile robots such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) are increasingly used for precision agriculture. While UGVs have larger payload capabilities and longer operation time, they are limited to 2-D space. This makes UAVs better suited for tasks that require fast coverage, harsh terrain traversal, and high altitude or multilevel operation. However, it remains a challenging task to develop a reliable yet fully autonomous UAV system that can actively extract actionable information in large-scale cluttered agricultural environments. Such a system will have to estimate its own poses, build a map of the environment, navigate through obstacles, and act to gather information with limited onboard computation and battery life. In this survey, we first review recent advances in UAV hardware and software, ranging from novel platforms and sensors to state-of-the-art autonomous navigation, object detection and segmentation, robot localization, and mapping algorithms related to agriculture. We then provide a list of challenges in each field and potential opportunities for the broader adoption of UAVs in precision agriculture.

Object Tracking-Based “Follow-Me” Unmanned Aerial Vehicle (UAV) System

The applications of information technology (IT) tools and techniques have, over the years, simplified complex problem solving procedures. But the power of automation is inhibited by the technicality in manning advanced equipment. To this end, tools deliberately combating this inhibition and advancing technological growth are the Unmanned Aerial Vehicles (UAVs). UAVs are rapidly taking over major industries such as logistics, security, and cinematography. Among others, this is a very efficient way of carrying out missions unconventional to humans. An application area of this technology is the local film industry which is not producing quality movies primarily due to the lack of technical know-how in utilizing these systems. This study therefore aim to devise an autonomous object tracking UAV system that would eliminate the complex procedure involved in stabilizing an aerial camera (aerial bot) midair and promote the creation of quality aerial video shooting. The study adopted Unified Modeling Language (UML) tools in modeling the system’s functionality. The traditional Server-Client model architecture was adopted. The OpenCV library employed proved highly efficient in aiding the tracking procedure. The system provided a usable web controller which provides easy interaction between the pilot and the drone. Conclusively, investments in UAVs would enhance creation of quality graphic contents.

MATHEMATICAL MODELING OF THE MPPT-CONTROLLER FOR RENEWABLE ENERGY SOURCES ON MOSFET TRANSISTORS

This article discusses field tests and practical implementation of a low-voltage LED lighting system with renewable energy sources in an autonomous facility and the development of a model for optimal temperature control in an autonomous facility. The method of complex management of the power supply system using the Smart controller of the energy supply of the autonomous object is also considered. To implement the mathematical model, the Simulink and SimPowerSystems software for visual modeling included in the MatLab package was used. The use of this software allows you to simulate complex electrical systems. The advantage of using this program is the combination of methods of structural and simulation modeling, and this approach provides the flexibility of the system for the model being developed, greatly simplifies the model, and therefore increases the speed of calculations. When developing indoor temperature control systems, a number of problems arise, such as determining the time required the temperature to rise to provide the set values to the required moment, choosing the temperature control algorithm and determining the parameters of the selected algorithm. The task of choosing the control law and the type of controller is to choose such a controller, which at minimum cost and maximum reliability would provide the specified quality of regulation. In this article, the choice was made on the PID regulator, since with a jump-like change of the regulated value, the PID regulator at the initial moment of time has an infinitely large influence on the object of regulation. Then the magnitude of the influence drops sharply to the value determined by the proportional component, after which the integral component of the regulator begins to exert its influence constantly. The transient process in PID controllers has minimal deviations in amplitude and time compared to P and PI controllers (i.e., the highest speed).

Особенности цифровизации в строительной отрасли как важный фактор ее устойчивого развития

This article determines that in the context of global digitalization, the competitiveness and sustainable development of companies depend on the speed of mastering new technologies. Assessment of the current level of the construction industry indicates its lag behind other industries. The aim of the study is to analyze the current level of digitalization of construction companies and summarize the constraining factors. The importance of continuous digitization of production and logistics, networking of autonomous smart objects or the use of self-learning systems in order to increase flexibility and optimize processes is emphasized. The main benefit of implementing digital business models is reducing the time it takes to make decisions, implement a project, and bring products to market. The factors holding back digital processes at the construction site are highlighted: a high proportion of manual production, over-regulation, dependence on the public sector and cyclical changes, the scale of the company. New technologies resulting from the fourth industrial revolution promise more efficient processes, greater time and cost savings, greater productivity and quality. The construction industry must catch up with other industries, because it also has to face the challenges of globalization, urbanization, climate change, resource scarcity, demographic change and other events that disrupt its sustainable development. Construction Site 4.0 promises improvements, but the fourth industrial revolution on the construction site is just beginning.

Algorithm for automatic compensation of thermal deformations of thermally loaded load-bearing structures

The paper considers a possible algorithm for the automatic control system of the thermal modes of load-bearing structures of the information-measuring system of autonomous objects. Thermo-deformation component of information-measuring error, which is the cause of distortion of operating and service information of an autonomous object, is reduced due to compensation of thermogradient by automatic control system of operation modes of distributed controlled heat sources. The system provides a significant reduction in the level of thermal deformation error of measurements, the cause of which is the deformation of supporting structures due to unstable and uneven heat release of information-measuring instruments placed on the structure. To compensate for thermal deformations, the system includes controlled heat sources that compensate for the thermal gradients of the supporting structure arising under the influence of the information-measuring system instruments and external thermal radiation on the structure. An effective rational control algorithm, providing compensation of the thermal gradient of the load-bearing structure to an acceptable level, is proposed. The control algorithm and the system structure are designed to be implemented by special software of the onboard computer.

Drawing on Architecture: The Object of Lines, 1970–1990

Drawing on Architecture: The Object of Lines, 1970–1990

Dynamic Object Tracking on Autonomous UAV System for Surveillance Applications.

The ever-burgeoning growth of autonomous unmanned aerial vehicles (UAVs) has demonstrated a promising platform for utilization in real-world applications. In particular, a UAV equipped with a vision system could be leveraged for surveillance applications. This paper proposes a learning-based UAV system for achieving autonomous surveillance, in which the UAV can be of assistance in autonomously detecting, tracking, and following a target object without human intervention. Specifically, we adopted the YOLOv4-Tiny algorithm for semantic object detection and then consolidated it with a 3D object pose estimation method and Kalman filter to enhance the perception performance. In addition, UAV path planning for a surveillance maneuver is integrated to complete the fully autonomous system. The perception module is assessed on a quadrotor UAV, while the whole system is validated through flight experiments. The experiment results verified the robustness, effectiveness, and reliability of the autonomous object tracking UAV system in performing surveillance tasks. The source code is released to the research community for future reference.

Intelligent automation in hospitality: exploring the relative automatability of frontline food service tasks

PurposeAutomation poses to change how service work is organized. However, there is a lack of understanding of how automation influences specific sectors, including specific hospitality jobs. Addressing this gap, this paper looks at the relative automatability of jobs and tasks which fall within one specific hospitality context: frontline food service.Design/methodology/approachStudy 1 analyzes the UK Office for National Statistics' Standard Occupational Classification (2020) data to determine the degree to which frontline food service jobs consist of tasks requiring mechanical, analytical, intuitive or empathetic intelligence. Study 2 contrasts these findings to current state of intelligent automation technology development through interviews and a focus group with food service technology experts (n = 13).FindingsOf all the tasks listed under food service in the ONS SOC 2020, 58.8% are found to require mechanical, 26.8% analytical, 11.3% intuitive and 3.1% empathetic intelligence. Further, the automatability of these tasks is found to be driven by three streams of technology development in particular: (1) autonomous navigation, (2) object manipulation and (3) natural language processing.Originality/valueHospitality management literature has started to conceptualize a move from mechanical and analytical service tasks to tasks centered around intuition and empathy. While previous studies have adopted a general view to what this might mean for hospitality jobs, this paper develops a novel, task-centric framework for Actioning Intelligent Automation in Frontline Food Service.

Drone-Based Autonomous Motion Planning System for Outdoor Environments under Object Detection Uncertainty

Recent advances in autonomy of unmanned aerial vehicles (UAVs) have increased their use in remote sensing applications, such as precision agriculture, biosecurity, disaster monitoring, and surveillance. However, onboard UAV cognition capabilities for understanding and interacting in environments with imprecise or partial observations, for objects of interest within complex scenes, are limited, and have not yet been fully investigated. This limitation of onboard decision-making under uncertainty has delegated the motion planning strategy in complex environments to human pilots, which rely on communication subsystems and real-time telemetry from ground control stations. This paper presents a UAV-based autonomous motion planning and object finding system under uncertainty and partial observability in outdoor environments. The proposed system architecture follows a modular design, which allocates most of the computationally intensive tasks to a companion computer onboard the UAV to achieve high-fidelity results in simulated environments. We demonstrate the system with a search and rescue (SAR) case study, where a lost person (victim) in bushland needs to be found using a sub-2 kg quadrotor UAV. The navigation problem is mathematically formulated as a partially observable Markov decision process (POMDP). A motion strategy (or policy) is obtained once a POMDP is solved mid-flight and in real time using augmented belief trees (ABT) and the TAPIR toolkit. The system’s performance was assessed using three flight modes: (1) mission mode, which follows a survey plan and used here as the baseline motion planner; (2) offboard mode, which runs the POMDP-based planner across the flying area; and (3) hybrid mode, which combines mission and offboard modes for improved coverage in outdoor scenarios. Results suggest the increased cognitive power added by the proposed motion planner and flight modes allow UAVs to collect more accurate victim coordinates compared to the baseline planner. Adding the proposed system to UAVs results in improved robustness against potential false positive readings of detected objects caused by data noise, inaccurate detections, and elevated complexity to navigate in time-critical applications, such as SAR.

Neural Networks With Disabilities: An Introduction to Complementary Artificial Intelligence.

Machine learning is a good tool to simulate human cognitive skills as it is about mapping perceived information to various labels or action choices, aiming at optimal behavior policies for a human or an artificial agent operating in the environment. Regarding autonomous systems, objects and situations are perceived by some receptors as divided between sensors. Reactions to the input (e.g., actions) are distributed among the particular capability providers or actuators. Cognitive models can be trained as, for example, neural networks. We suggest training such models for cases of potential disabilities. Disability can be either the absence of one or more cognitive sensors or actuators at different levels of cognitive model. We adapt several neural network architectures to simulate various cognitive disabilities. The idea has been triggered by the "coolability" (enhanced capability) paradox, according to which a person with some disability can be more efficient in using other capabilities. Therefore, an autonomous system (human or artificial) pretrained with simulated disabilities will be more efficient when acting in adversarial conditions. We consider these coolabilities as complementary artificial intelligence and argue on the usefulness if this concept for various applications.

PHILOSOPHY OF THE MODERN TEXT: THE FEATURES OF THE NARRATIVE STRUCTURE

The article deals with the problem of the philosophy of the text as a complex episteme of modern humanitarian discourse. The issue of the specifics of the narrative structure, the polyphony of the text in the dialogical space of modern literary discourse is actualized. It is proposed to consider the text in two aspects: the text as an autonomous object of reflection and the text as a code. Literary practices are investigated from the point of view of identifying mechanisms for the implementation of a given narrative structure and a voluminous descriptive plan of the text.The production of metatext is becoming one of the most significant trends in modern Kazakh prose, especially the novel genre. Special attention is paid to the analysis of the nuclear concepts of the narrative and their interaction with other elements of the poetics of the text. It is determined that the narrative frame of the text can be formed linearly and linearly. The philosophy of the text is inextricably linked with the general narratological postulate of eventfulness and a specific hierarchy of events, characters in the work. It is determined that the conceptual task of Kazakh historical romance is a panoramic examination of the complex historical and cultural ties of ancient nomadic and sedentary states. A combination of the traditional lyric-epic, realistic and postmodern aspects, the interaction of ethno-and foreign-cultural elements within one text is investigated. This approach determines the style of the text, deepening its philosophical and worldview content.Jamie E. Carroll's idea of ​​“transition from the text as a complete work to the text” with potentially maximum wide interpretive and communicative freedom seems to be productive when considering the philosophy of the text, its narrative specificity. In this case, the emergence of texts with a predominantly hybrid genre-style nature (novel-essay, novel-requiem, journalistic story, etc.) is possible.

Simulation of the Operation of Lithium-Ion Batteries in the Power-Supply System of Autonomous Objects

Simulation of the Operation of Lithium-Ion Batteries in the Power-Supply System of Autonomous Objects

The scope of the pramāṇas in classical and postclassical Sāṃkhya

ABSTRACT One of the lively polemics between Buddhists and Naiyāyikas is devoted to the question of whether each pramāṇa—means of knowledge—has an independent scope of validity, which does not overlap the scopes of other pramāṇas, or whether more than one pramāṇa can be applied to the same object. Dignāga and continuators of his thought defend pramāṇa-vyavasthā, ‘autonomy of [the object spheres of] pramāṇas,’ while Naiyāyikas defend the opposing conception, called pramāṇa-samplava, ‘coalescence of [the object spheres of] pramāṇas.’ Scholars usually ascribe pramāṇa-vyavasthā to Sāṃkhya. This paper explores the classical and postclassical Sāṃkhya view of the scope of the pramāṇas and shows that Sāṃkhya did not follow pramāṇa-vyavasthā. In Sāṃkhya, the scopes of perception and inference for knowing perceptible objects overlap, while inference for knowing supersensible objects and reliable verbal testimony have autonomous object spheres. However, there is also a tendency toward pramāṇa-vyavasthā in Sāṃkhya, which is in conflict with the Sāṃkhya theory of pramāṇas.

Intelligent data processing methods in sensor networks of mobile and autonomous objects

In the near term, tasks related to monitoring mobile geographically distributed objects with the aim of efficiently managing them are acquiring great importance. An example of such tasks is the monitoring the state of given number of vehicles of agricultural enterprise, when it becomes necessary to promptly transfer given amount of data with high requirements for the level of their reliability. The use of the infrastructure of cellular mobile networks for this is not suitable for a number of reasons for rural areas. The paper proposes an approach based on the use of high-speed dynamic sensor networks. This makes it possible to carry out relay transmission of data between objects, including mobile ones. However, the issues of building flexible data transfer protocols in networks of this kind, providing a significant data transfer rate and taking into account the priority of the transmitted information and its features, still remain open. At the same time, for mobile objects in conditions of non-stationarity of the parameters of communication channels, the problems of ensuring the required reliability of data are of particular importance. To solve the last problem, it is proposed to use the permutation decoding method based on the cognitive metaphor.

Vision-Based Robotic Arm Control Algorithm Using Deep Reinforcement Learning for Autonomous Objects Grasping

While working side-by-side, humans and robots complete each other nowadays, and we may say that they work hand in hand. This study aims to evolve the grasping task by reaching the intended object based on deep reinforcement learning. Thereby, in this paper, we propose a deep deterministic policy gradient approach that can be applied to a numerous-degrees-of-freedom robotic arm towards autonomous objects grasping according to their classification and a given task. In this study, this approach is realized by a five-degrees-of-freedom robotic arm that reaches the targeted object using the inverse kinematics method. You Only Look Once v5 is employed for object detection, and backward projection is used to detect the three-dimensional position of the target. After computing the angles of the joints at the detected position by inverse kinematics, the robot’s arm is moved towards the target object’s emplacement thanks to the algorithm. Our approach provides a neural inverse kinematics solution that increases overall performance, and its simulation results reveal its advantages compared to the traditional one. The robot’s end grip joint can reach the targeted location by calculating the angle of every joint with an acceptable range of error. However, the accuracy of the angle and the posture are satisfied. Experiments reveal the performance of our proposal compared to the state-of-the-art approaches in vision-based grasp tasks. This is a new approach to grasp an object by referring to inverse kinematics. This method is not only easier than the standard one but is also more meaningful for multi-degrees of freedom robots.

Convolutional Neural Network Using for Multi-Sensor 3D Object Detection

The purpose of this article is to detect 3D objects inside the independent vehicle with great accuracy. The method proposed a Multi-View 3D System (MV3D) framework which encodes the sparse 3d-point cloud with a compact multi-view image, using LIDAR satellite image and RGB pictures as inputs, and predicts 3D boundary boxes. The network comprises two sub-networks: one for creating 3D artifacts and one for multi-visual fusion functionality. Propose an autonomous 3D object tracking approach to manipulate sparse and dense knowledge about romanticizing and geometry in stereo images. The Stereo R-CNN strategy applies Faster R-CNNs to stereo inputs such that objects are simultaneously identified and linked in conservative and liberal images. Such charts were then combined and fed into a 3D proposal generator to generate accurate 3D proposals for vehicles. In the second step, the refining network extended the features of the proposal regions further and carried through the classification, regression of a 3D package box, and guidance estimates, to predict vehicle location and heading in 3D area and add additional branches after the stereo region Proposal Network (RPN).

Phase synchronization in the system of supply voltage parameters correction by the adaptive filtration method

An adaptive phase-locked loop is considered, which makes it possible to improve the stability of synchronous active filters, to achieve compensation for high-quality harmonic components of the current consumed by autonomous objects. Therefore, the use of such an active filter will improve the power quality and the normal trouble-free operation of the equipment in general. A control system with an adaptive phase-locked loop often has the advantages of a reliable and efficient control system. It makes it possible to quickly respond to dynamic changes in the load, which is typical for the operation of functional equipment of autonomous objects. The control system becomes more flexible, reliable, efficient and provides an instantaneous value of the compensation current from the measured values of the load current curve. Calculations can be carried out in real time. LMS, NLMS, RLS algorithms are considered as adjusting the weighted adaptive phase-locked loop in the system for correcting the supply voltage parameters. Based on the simulation of algorithms carried out in the MATLAB environment, a comparative analysis of their effectiveness is made. It is shown that the NLMS algorithm has the highest suppression quality and minimum transient time. The NLMS algorithm works in real time and is recommended for use in the supply voltage correction system.

Knowledge Graph Representation Fusion Framework for Fine-Grained Object Recognition in Smart Cities

Autonomous object detection powered by cutting-edge artificial intelligent techniques has been an essential component for sustaining complex smart city systems. Fine-grained image classification focuses on recognizing subcategories of specific levels of images. As a result of the high similarity between images in the same category and the high dissimilarity in the same subcategories, it has always been a challenging problem in computer vision. Traditional approaches usually rely on exploring only the visual information in images. Therefore, this paper proposes a novel Knowledge Graph Representation Fusion (KGRF) framework to introduce prior knowledge into fine-grained image classification task. Specifically, the Graph Attention Network (GAT) is employed to learn the knowledge representation from the constructed knowledge graph modeling the categories-subcategories and subcategories-attributes associations. By introducing the Multimodal Compact Bilinear (MCB) module, the framework can fully integrate the knowledge representation and visual features for learning the high-level image features. Extensive experiments on the Caltech-UCSD Birds-200-2011 dataset verify the superiority of our proposed framework over several existing state-of-the-art methods.

Inaugurating the “White Passage”: Art ‘76

AbstractWithin an art exhibition, the disposition of space is fundamental in experiencing artworks. A study of the exhibition space as discourse enmeshes art within a framework of relationship and processes instead of viewing art as an isolated and autonomous object. This paper features the case study of Art ‘76, the inaugural exhibition of Singapore's first large-scale institution of art, the National Museum Art Gallery (NMAG). The NMAG's opening in 1976 had been much anticipated by artists and the art audience since the 1960s, it was also an important milestone in the National Museum of Singapore's process of modernisation and revitalisation. During Singapore's post-independent period, the National Museum began to redefine itself as a civic museum focussing on Singapore's history and culture, shifting away from its previous incarnation of a research-focused colonial institution, the Raffles Library and Museum. Singapore was not alone in exploring the role of modern art in nation-building, as neighbouring Southeast Asian countries such as Indonesia, Philippines, Malaysia and Thailand also began to moot for their own institution of modern art around the same period of time. Art ‘76 and the NMAG represent a case of distinct spatial typology that arose out of unique institutional and socio-political dynamic in post-independent Singapore. In analysing the legacy as well as the relationships and contentions that shaped the spatial articulation of Art ‘76, this paper studies existing visual and oral archive, as well as critically evaluating the concepts of space as a subject of historical study.

Autonomous Vision-Guided Object Collection From Water Surfaces With a Customized Multirotor

This article presents a multirotor system with an integrated net mechanism for autonomous object detection and collection from water surfaces utilizing only onboard sensors. The task of object collection on water surfaces is challenging due to the following reasons: 1) propeller outwash alters the object's dynamics; 2) unpredictable current flows, 3) extreme reflection and glare off water surfaces affect the object detection; and 4) noisy height measurements over water surface. A two-phase object-detection algorithm is developed with a linearized polarization filter and specularity removal algorithm to eliminate reflections and an edge-based contour detector for detection of objects on water surface. Subsequently, a boundary layer sliding-mode control is implemented to ensure the system is robust to modeling uncertainties. A dynamic sliding surface is designed based on constrained linear model predictive control. The efficacy of the proposed collection system is validated by multiple outdoor tests. Multiple objects of different shapes and sizes are collected with an overall success rate of 91.6%.