Autonomous Architecture Research Articles

GreenHopper: The Danish spearhead towards autonomous waterborne mobility

Abstract GreenHopper is the first Danish zero-emission ferry developed as a test platform for autonomous waterborne navigation technologies. The paper presents technology development within the innovation project ShippingLab Autonomy, which led to the commissioning of GreenHopper at Limfjorden (DK) in December 2022. The technology research resulted in a holistic system architecture for surface vessel autonomy, based on distribution of functionality and responsibility on software modules, similar to the structure observed in the International Maritime Organization (IMO) Seafarers Training Certification and Watch-keeping (STCW) regulatory framework. The paper shows how this approach results in an architecture that supports safe behaviours of individual modules and of autonomous navigation at a system level. The paper presents the individual modules, specific features and benefits. Elements of the regulatory framework are highlighted to poise technology approval by maritime authorities. The paper reflects on lessons learned, discusses continued technology validation in dedicated operational scenarios.

Voxel-based modular architectural design strategy toward autonomous architecture

Voxel-based modular architectural design strategy toward autonomous architecture

Time as a Founding Factor in Architectural Thought

The research dealt with the concepts of time and architectural thought and the extent of the influence of Ideas derived from the element of time on the variation and differentiation of architectural movements and schools, by reviewing a group of vocabulary such as nostalgia, present, and looking forward to the future, the null of the present and immortality in architecture and the null or deferred future, and the study of the duration of its reflection on architectural thought to lead to the differentiation of each of the architecture of Mesopotamia, Classical architecture, Modern architecture, Post-modernism, and Autonomous architecture, Deconstruction architecture according to these terms. The problem of the research was the lack of clarity on the influence of the element of time and its role in the differentiation of architectural thought. The main goal of the research is to focus on the role of the element of time in the differentiation and uniqueness of architectural thought. As for the research hypothesis, it focused on emphasizing the role of thought that distinguishes time in the differentiation of architectural thought, which in turn guarantees the uniqueness of societies, and the most important finding of the research is that Classical architecture is distinguished by its interest in the principle of nostalgia, and that there are some trends in Contemporary Iraqi Architecture based on the principle of nostalgia represented by nostalgia for formal elements, and that modern architecture urged in most of its buildings nostalgia for the present.

Unmanned Underwater Vehicle Autonomy and Control near Submarines Using Actively Sampled Surrogates

Many tools have been developed to simulate unmanned underwater vehicle (UUV) motion and autonomous behaviors to evaluate UUV capabilities. However, there is no simulator that performs real-time modeling of the complex hydrodynamic interaction forces that a UUV experiences when operating near a moving submarine. These hydrodynamic interactions must be determined in real time to simulate the launch and recovery of UUVs from submarines. Potential flow models may be fast enough to solve the hydrodynamic interactions in real time, but by oversimplifying the physics and neglecting viscosity, they introduce inaccuracies into the simulations. Computational fluid dynamics (CFD) is capable of accurately modeling these hydrodynamic interactions, but simulations take hours or days to solve. To overcome this obstacle, a machine learning method known as Gaussian process (GP) regression is used to create a surrogate reduced-order-model that predicts the hydrodynamic interactions in real time. The GP regression model is trained by actively sampling CFD simulations in order to accurately model complex hydrodynamic interactions. This new approach allows the GP regression model to be incorporated into a UUV motion simulator and evaluate how the UUV is affected by the hydrodynamic interactions. Operating envelopes are developed that outline regions where the UUV safely overcomes the hydrodynamic interactions and where the UUV is overpowered and collides with the submarine. By incorporating this surrogate model into the autonomy architecture, new autonomous behaviors are created that compensate for the hydrodynamic interactions by adjusting the desired UUV heading and speed which allows it to better stay on course.

Contra assertions, feedback improves word recognition: How feedback and lateral inhibition sharpen signals over noise

Whether top-down feedback modulates perception has deep implications for cognitive theories. Debate has been vigorous in the domain of spoken word recognition, where competing computational models and agreement on at least one diagnostic experimental paradigm suggest that the debate may eventually be resolvable. Norris and Cutler (2021) revisit arguments against lexical feedback in spoken word recognition models. They also incorrectly claim that recent computational demonstrations that feedback promotes accuracy and speed under noise (Magnuson et al., 2018) were due to the use of the Luce choice rule rather than adding noise to inputs (noise was in fact added directly to inputs). They also claim that feedback cannot improve word recognition because feedback cannot distinguish signal from noise. We have two goals in this paper. First, we correct the record about the simulations of Magnuson et al. (2018). Second, we explain how interactive activation models selectively sharpen signals via joint effects of feedback and lateral inhibition that boost lexically-coherent sublexical patterns over noise. We also review a growing body of behavioral and neural results consistent with feedback and inconsistent with autonomous (non-feedback) architectures, and conclude that parsimony supports feedback. We close by discussing the potential for synergy between autonomous and interactive approaches.

An autonomous architecture based on reinforcement deep neural network for resource allocation in cloud computing

An autonomous architecture based on reinforcement deep neural network for resource allocation in cloud computing

Time-sensitive autonomous architectures

Time-sensitive autonomous architectures

Thermal management system in electric vehicle batteries for environmental sustainability

AbstractDue to the extreme sensitivity of temperature in Li‐ion batteries, thermal management is a significant issue that must be addressed. Since the battery in electric vehicles produces an enormous amount of heat, it reduces its efficiency and its performance. Currently, there is a need for electric vehicles (EVs) because conventional IC engines produce an enormous amount of pollution which affects the environment, so an electric vehicle produces a very small amount of pollution. It is now being recommended and used by many people. But the electric vehicle faces some major problems due to overheating in their battery module. Nowadays, battery temperature is regulated by a system called battery thermal management system (BTMS). Modern EVs use active and passive cooling systems. Thermal management tries to improve battery architecture for greater autonomy or quick charging. To meet future difficulties in thermal management, such as air or liquid cooling, are needed. As a result of the battery's overheating, the vehicle's performance, power, energy storage, charging, and discharging are all negatively impacted; hence, a reliable thermal management system for the battery is essential for resolving these problems. This study provides an overview of the BTMS of the future, beginning with the problems involving temperature and safety. The following is a list of the benefits and drawbacks of BTMSs, which are used to maintain acceptable temperatures for battery packs. In conclusion, an analysis of the progress made in developing temperature management systems for future batteries is presented. As a first look at potential BTMSs for locomotive applications, it has been proposed to conduct a comprehensive analysis and classification of both existing and potential battery management systems.

A Study on Object Detection and Tracking of a Mobile Robot Using CIE L^* a^* b^* Color Space

Autonomous vehicles are increasingly used in daily life and industrial applications. Mobile robot technologies lead to autonomous architectures in these areas. The path planning methods of mobile robots contain differences in the purpose they realize. This trajectory planning from a determined starting point to the target point brings many techniques from image processing to artificial intelligence. In the study, an application with a unique design has been carried out on the tracking of circular objects with different diameters and colors by a mobile robot. Moving object is detected with CIE L^* a^* b^* color space with RGB-D camera by utilizing the ROS server-client architecture. The mobile robot tracks the detected object at a certain distance at a constant speed. Image filtering parameters are processed by the mobile robot in the Matlab environment together with the publisher-subscriber parameters. Thus, two circular objects with different colors, detected because of image processing and determined beforehand, are continuously followed by the mobile robot at a certain speed. Experiments were carried out using different diameter, size tolerance and color parameters in the image depending on the CIE L^* a^* b^* color space.

An Energy-Based Control Architecture for Shared Autonomy

In robotic applications where the autonomy is shared between the human and the robot, the autonomous behavior of the robotic system is determined considering mainly the task to be executed and the data collected from the environment using, e.g., formal methods and machine learning techniques. Nevertheless, it is important to correctly translate high-level decision into low-level control inputs in order to avoid an unstable behavior due to a naive implementation of the autonomy. In this article, we propose an energy-based architecture for shared autonomy that allows to reproduce as closely as possible the desired behavior, while ensuring a robust stability of the robotic system. The proposed architecture is experimentally validated in two application scenarios: shared control of a multirobot system and variable admittance control in human robot collaboration

Autonomous Houses and Architecture of Cybernetics in the 1970s: Towards Limits and Undeveloped Potentials of the Sustainable

In 1969, English researcher Gordon Pask published an article named “The Architectural Relevance of Cybernetics”, defining a theoretical framework concerning a cybernetic theory of architecture. Throughout the 1970s, the Cambridge Research Group designed the Autonomous House, a self-sufficient dwelling in terms of energy and food. Part of the Cambridge group approach relates to cybernetics. However, the group did not regard several aspects of cybernetics described in the theoretical framework of Pask. Through a literature review primarily focused on 1970s architectural magazines, this paper analyses which cybernetic aspects were not regarded in the Cambridge Autonomous House and other similar houses as case studies. Through an innovative analytical method, it demonstrates that some limitations of the house design, such as the main focus on costs and technologies, could have been reduced if aspects of cybernetics had been more incorporated. Using cybernetics as a lens represents a method which can be beneficial also in analysing today’s examples of sustainable and autonomous architecture.

Multimodality robotic systems: Integrated combined legged-aerial mobility for subterranean search-and-rescue

This work presents a field-hardened autonomous multimodal legged-aerial robotic system for subterranean exploration, extending a legged robot to be the carrier of an aerial platform capable of a rapid deployment in search-and-rescue scenarios. The driving force for developing such robotic configurations are the requirements for large-scale and long-term missions, where the payload capacity and long battery life of the legged robot is combined and integrated with the agile motion of the aerial agent. The multimodal robot is structured around the quadruped Boston Dynamics Spot, enhanced with a custom configured autonomy sensor payload as well as a UAV carrier platform, while the aerial agent is a custom built quadcopter. This work presents the novel design and hardware implementation as well as the onboard sensor suites. Moreover it establishes the overall autonomy architecture in a unified supervision approach while respecting each locomotion modality, including guidance, navigation, perception, state estimation, and control capabilities with a focus on rapid deployment and efficient exploration. The robotic system complete architecture is evaluated in real subterranean tunnel areas, in multiple fully autonomous search-and-rescue missions with the goal of identifying and locating objects of interest within the subterranean environment.

EQ-RPL: An Energy-Efficient and Quality-Aware Routing Protocol for IoT-Based Low-Power and Lossy Networks

<p>In recent years, the advances in sensing and communication technologies have led to the rapid development of various applications of the Internet of Things (IoT). The devices in IoT form an autonomous network architecture, in which the device has a limited battery power and the link has a low reliability. This kind of network is called the low-power and lossy network. In this paper, we propose a routing protocol for low-power and lossy networks. The proposed protocol introduces a novel rank value to construct a proper destination-oriented directed acyclic graph for the source node to transmit packets to the destination node. The proposed rank value is mainly derived from the expected transmission count, which is widely used to represent the link quality. Moreover, we consider the residual energy as the metric for a node to select the proper node to relay the packet to the destination node. We conducted simulations for performance evaluation, showing that the proposed routing protocol improves the packet delivery ratio, especially for the environment with a high bit error rate. The result also validated that our approach achieves the balance of energy consumption of nodes, compared to the existing approach.</p> <p> </p>

A Survey on LoRaWAN Technology: Recent Trends, Opportunities, Simulation Tools and Future Directions

Low-power wide-area network (LPWAN) technologies play a pivotal role in IoT applications, owing to their capability to meet the key IoT requirements (e.g., long range, low cost, small data volumes, massive device number, and low energy consumption). Between all obtainable LPWAN technologies, long-range wide-area network (LoRaWAN) technology has attracted much interest from both industry and academia due to networking autonomous architecture and an open standard specification. This paper presents a comparative review of five selected driving LPWAN technologies, including NB-IoT, SigFox, Telensa, Ingenu (RPMA), and LoRa/LoRaWAN. The comparison shows that LoRa/LoRaWAN and SigFox surpass other technologies in terms of device lifetime, network capacity, adaptive data rate, and cost. In contrast, NB-IoT technology excels in latency and quality of service. Furthermore, we present a technical overview of LoRa/LoRaWAN technology by considering its main features, opportunities, and open issues. We also compare the most important simulation tools for investigating and analyzing LoRa/LoRaWAN network performance that has been developed recently. Then, we introduce a comparative evaluation of LoRa simulators to highlight their features. Furthermore, we classify the recent efforts to improve LoRa/LoRaWAN performance in terms of energy consumption, pure data extraction rate, network scalability, network coverage, quality of service, and security. Finally, although we focus more on LoRa/LoRaWAN issues and solutions, we introduce guidance and directions for future research on LPWAN technologies.

Metamachines of pluripotent colloids

Machines enabled the Industrial Revolution and are central to modern technological progress: A machine’s parts transmit forces, motion, and energy to one another in a predetermined manner. Today’s engineering frontier, building artificial micromachines that emulate the biological machinery of living organisms, requires faithful assembly and energy consumption at the microscale. Here, we demonstrate the programmable assembly of active particles into autonomous metamachines using optical templates. Metamachines, or machines made of machines, are stable, mobile and autonomous architectures, whose dynamics stems from the geometry. We use the interplay between anisotropic force generation of the active colloids with the control of their orientation by local geometry. This allows autonomous reprogramming of active particles of the metamachines to achieve multiple functions. It permits the modular assembly of metamachines by fusion, reconfiguration of metamachines and, we anticipate, a shift in focus of self-assembly towards active matter and reprogrammable materials.

Dynamic Allocation of SDN Controllers in NFV-Based MEC for the Internet of Vehicles

The expected huge amount of connected cars and applications with varying Quality of Service (QoS) demands still depend on agile/flexible networking infrastructure to deal with dynamic service requests to the control plane, which may become a bottleneck for 5G and Beyond Software-Defined Network (SDN) based Internet of Vehicles (IoV). At the heart of this issue is the need for an architecture and optimization mechanisms that benefit from cutting edge technologies while granting latency bounds in order to control and manage the dynamic nature of IoV. To this end, this article proposes an autonomic software-defined vehicular architecture grounded on the synergy of Multi-access Edge Computing (MEC) and Network Functions Virtualization (NFV) along with a heuristic approach and an exact model based on linear programming to efficiently optimize the dynamic resource allocation of SDN controllers, ensuring load balancing between controllers and employing reserve resources for tolerance in case of demand variation. The analyses carried out in this article consider: (a) to avoid waste of limited MEC resources, (b) to devise load balancing among controllers, (c) management complexity, and (d) to support scalability in dense IoV scenarios. The results show that the heuristic efficiently manages the environment even in highly dynamic and dense scenarios.

Design of System Level Architecture of Multi-Core with Array Mapping Based on Floating Processing Factor-Fast Fourier Transform for Health Informatics Application

In FFT algorithms memory access patterns prevent multiple architectures from achieving high machine use, particularly when parallel processing is needed to achieve the desired efficiency rates. Beginning with the extremely powerful FFT heart, the on-chip memory hierarchy for the multicored FFT processor, is co-designed and linked on-chip. We have shown that the Floating Processing Factor (FPPE) proposed achieves greater operating rate and lower power for the application of health informatics. This test mechanism aids in omission of faulty cores and autonomous detection also makes elegant multi-core architecture degradation feasible. Experimental results illustrate that the anticipated design is scalable widely in terms of performance overhead and hardware overhead which makes it appropriate to many-cores with more than a thousand processing cores through Low Power and High Speed.

Fault-Adaptive Autonomy in Systems with Learning-Enabled Components.

Autonomous Cyber-Physical Systems (CPS) must be robust against potential failure modes, including physical degradations and software issues, and are required to self-manage contingency actions for these failures. Physical degradations often have a significant impact on the vehicle dynamics causing irregular behavior that can jeopardize system safety and mission objectives. The paper presents a novel Behavior Tree-based autonomy architecture that includes a Fault Detection and Isolation Learning-Enabled Component (FDI LEC) with an Assurance Monitor (AM) designed based on Inductive Conformal Prediction (ICP) techniques. The architecture implements real-time contingency-management functions using fault detection, isolation and reconfiguration subsystems. To improve scalability and reduce the false-positive rate of the FDI LEC, the decision-making logic provides adjustable thresholds for the desired fault coverage and acceptable risk. The paper presents the system architecture with the integrated FDI LEC, as well as the data collection and training approach for the LEC and the AM. Lastly, we demonstrate the effectiveness of the proposed architecture using a simulated autonomous underwater vehicle (AUV) based on the BlueROV2 platform.

A Theoretical Discussion and Survey of Network Automation for IoT: Challenges and Opportunity

The introduction of the Internet of Things (IoT) and massive machine-type communications has implied an increase in network size and complexity. In particular, there is already a huge number of IoT devices in the market in various sectors, such as smart agriculture, smart city, smart home, smart transportation, etc. The IoT interconnectivity technologies are also increasing. Therefore, these are increasingly overwhelming the efforts of network administrators as they try to design, reconfigure and manage such networks. Relying on humans to manage such complex and dynamic networks is becoming unsustainable. Network automation promises to reduce the cost of administration and maintenance of network infrastructure, by offering networks the capability to manage themselves. Network automation is the ability of the network to manage itself. Various standardization organizations are taking the initiative in introducing network automation, such as European Telecommunication Standardization Institute (ETSI). ETSI is leading the standardization activities for network automation. It has provided different versions of reference architecture called generic autonomic network architecture (GANA), which describes a four-level abstraction for network-management decision elements (DEs), protocol level, function level, node level, and network level. In this article, we review and survey the existing works before and after the introduction of software-defined networking (SDN) and network-function-virtualization (NFV). We relate the main trending paradigms being followed, such as SDN, NFV, machine learning (ML), microservices, multiagent system (MAS), containerization, and cloudification, as a pivotal enabler of full network automation. We also discuss the autonomic architectures proposed in the literature. Finally, we presented possible future research directions and challenges that need to be tackled to progress in achieving full network automation.

A Data-Fusion-Assisted Telemetry Layer for Autonomous Optical Networks

For further improving the capacity and reliability of optical networks, a closed-loop autonomous architecture is preferred. Considering a large number of optical components in an optical network and many digital signal processing modules in each optical transceiver, massive real-time data can be collected. However, for a traditional monitoring structure, collecting, storing and processing a large size of data are challenging tasks. Moreover, strong correlations and similarities between data from different sources and regions are not properly considered, which may limit function extension and accuracy improvement. To address abovementioned issues, a data-fusion-assisted telemetry layer between the physical layer and control layer is proposed in this paper. The data fusion methodologies are elaborated on three different levels: Source Level, Space Level and Model Level. For each level, various data fusion algorithms are introduced and relevant works are reviewed. In addition, proof-of-concept use cases for each level are provided through simulations, where the benefits of the data-fusion-assisted telemetry layer are shown.