Full Autonomy Research Articles

The Haidou‐1 hybrid underwater vehicle for the Mariana Trench science exploration to 10,908 m depth

AbstractAn unmanned Autonomous and Remotely Operated Vehicle (ARV), Haidou‐1, visited the Challenger Deep in the Mariana Trench, and performed observation, sampling and bathymetric mapping explorations at the trench bottom. The Haidou‐1 vehicle reached a depth of 10,908 m in the west pool of the Challenger Deep and probed a depth of 10,909 m in the east pool. The 2600 kg underwater robotic vehicle could conduct survey missions with full autonomy and can also be remotely operated through a light fiber tether. Haidou‐1 carries an electric manipulator to implement lightweight intervention tasks. The fiber‐optical tether enables long‐distance real‐time high‐bandwidth communication at full‐ocean depth, thereby providing situational awareness and remote intervention. The hybrid concept we defined for the Haidou‐1 vehicle refers to three typical working modes: Autonomous Underwater Vehicle mode, Remotely Operated Vehicle mode, and ARV mode. There is no need to change any structural configuration at sea to meet the needs of multidisciplinary oceanographic investigation. This paper reports the overview design of Haidou‐1. Practical field trials at the Challenger Deep were conducted to validate the feasibility and performance of the developed system. In the aggregate, eight dives exceeded 10,000 m counting all three operation modes. Some of the initial results are presented including the high‐resolution bathymetric map created by Haidou‐1 onboard sonar, and no similar results have been found yet.

Low‐Temperature Flexible Integration of All‐Solid‐State Thin‐Film Lithium Batteries Enabled by Spin‐Coating Electrode Architecture

AbstractMicro energy sources as the nucleus of intelligent microdevices guarantee their full autonomy in the dimensions of time and space. However, the state‐of‐the‐art micro energy storage components, like all‐solid‐state thin‐film microbatteries (ASSTFBs), whose direct integration is impeded by the stereotyped vacuum‐based manufacturing technologies, for which an inevitable high‐temperature annealing step (> 500 °C) can exert catastrophic effects on the attached microdevices during the crystallization of manufactured insertion thin‐film cathodes, especially in flexible integration. Herein, a prototype construction is created to benchmark concrete feasibility for the low‐temperature manufacturing of ASSTFBs via a nonvacuum‐based spin‐coating electrode architecture. Results show that the spin‐coated LiFePO4 films enable low‐temperature (≈ 45 °C) manufacturing of ASSTFBs, by which it can deliver excellent cycling performance up to 1000 cycles. Importantly, this technology presents the versatility of integrating various cathode composites into ASSTFBs and is therefore generalized to the LiCoO2‐ and Li4Ti5O12‐based solid‐state chemistries. Furthermore, ASSTFBs with such compliant electrodes manifest outstanding flexibility without pronounced capacity degradation by successfully integrating on flexible temperature‐sensitive substrates. The spin‐coating protocol provides a general solution for excessive processing temperatures and ample opportunities for the development of on‐chip integratable and flexible ASSTFBs.

Application of deep learning in image processing of unmanned vehicles

Artificial Intelligence has accelerated research on autonomous vehicles in the past few years. However, it is not easy to achieve full autonomy on account of the essence of a complex and dynamic driving environment. Fortunately, the rapid development of deep learning has made great progress, which can be used to solve problems about image processing in the autonomous vehicles field. This paper offers a comprehensive review of the recent deep-learning-based image processing methods that leverage data detected. The paper gives a brief overview of deep learning, discussing basic concepts and principles. We also discuss the common models and architectures of deep learning and introduce typical deep learning techniques: convolutional neural networks (CNN). Furthermore, we divided the application of deep learning in the autonomous vehicles into three parts and discuss them respectively. Finally, we review the disadvantages of the application of deep learning in image processing for autonomous vehicles. On this basis, we put forward our insights and point out promising research directions.

Consensus on the content of an instrument to measure person-centred teamwork: An e-Delphi study.

To establish consensus on items to be included in an instrument to measure person-centred teamwork in a hospital setting. The objective was to identify the items through a methodological literature review. Refine the items and obtain consensus on the items. A definition and related attributes of person-centred teamwork have been agreed upon. An instrument is needed to measure and monitor person-centred teamwork in hospital settings. Consensus, electronic Delphi design. Items were identified through a methodological literature review. These items were included in three electronic Delphi rounds. Using purposive and snowball sampling, 16 international experts on person-centred care, teamwork and/or instrument development were invited to participate in three electronic Delphi rounds via Google Forms. Descriptive statistics were used to demonstrate their agreement on the relevance and clarity of each item. Items were included if consensus was 0.75. Content analysis was used to analyse written feedback from experts. The response rate was 56% (n = 9/16). Nine experts participated over an 8-week period to reach consensus on the items to be included in an instrument to measure person-centred teamwork in hospital settings. The experts' responses and suggestions for rephrasing, removing and adding items were incorporated into each round. A Delphi consensus exercise was completed, and experts reached agreement on 38 items to be included in an instrument that can be used to evaluate person-centred teamwork in hospital settings. We engaged with nine international experts in the academic and clinical field of person-centeredness, teamwork and/or instrument development. An online platform was used to allow the experts to give input into the study. The experts engaged from their own environment with full autonomy and anonymity. Person-centred teamwork, aimed at improving practice is now measurable. Person-centred teams improve outcomes of patients. Person-centred teamwork was specifically developed to assist low compliance areas in hospitals.

Hybrid Navigation Acceptability and Safety

Autonomous vessels have emerged as a prominent and accepted solution, particularly in the naval defence sector. However, achieving full autonomy for marine vessels demands the development of robust and reliable control and guidance systems that can handle various encounters with manned and unmanned vessels while operating effectively under diverse weather and sea conditions. A significant challenge in this pursuit is ensuring the autonomous vessels' compliance with the International Regulations for Preventing Collisions at Sea (COLREGs). These regulations present a formidable hurdle for the human-level understanding by an autonomous systems as they were originally designed from common navigation practices created since the mid-19th century. Their ambiguous language assumes experienced sailors' interpretation and execution and, therefore, demands a high-level (cognitive) understanding of language and agent intentions that are beyond the capabilities of current state-of-the-art of intelligent system. This position paper highlights the critical requirement of a trustworthy control and guidance system and explores the complexities of adapting COLREGs for safe vessel-on-vessel encounters considering autonomous maritime technology competing and/or cooperating with manned vessels.

Legal Personality of Robots

Developing a well-defined legal framework for robots is vital in this age of rapid advancement in technology. Such regulation is important not only to protect patient rights, but also to encourage responsible technological innovation and maximize the potential of robotics. In my research on the legal personality for robots, given the novelty of the topic and scarcity of specialized references, the research was conducted through extrapolating and analyzing related systems and regulations in the field of technology, in addition to studying relevant academic research on legal personality. A range of perspectives and trends were reviewed regarding granting legal personality to robots. The research began with the topic of legal personality in general, then discussed the notion of granting legal personality to robots between proponents and opponents. It also examined the position of countries and international organizations on robot legal personality, which have not yet recognized independent robots as legal persons since robots do not possess finances separate from their manufacturing companies, nor full autonomy from their human makers and operators. It was emphasized that granting legal personality to any entity requires a specific criterion which is the capacity to acquire rights and duties, assume obligations, and legal personality for robots is mainly attributed to the principle of appropriateness, legal necessity and their ability to act with a degree of consciousness and independence, which reinforces the likelihood of their committing harmful acts, causing damage to others. Given the treatment of robots in most countries as objects, the European Parliament put forward the human agent theory. Therefore, legislators should intervene to establish a clear legal framework that defines the legal nature of robots in a way that protects patient interests without discouraging companies and inventors from innovating to maximize the benefits of robotics and artificial intelligence technologies.

Political Interference and Tertiary Institutions in Nigeria

This paper discussed the implication of political interference on tertiary institutions in Nigeria. Secondary data was used in the paper. The data were collected from print and online publications. The paper revealed the implication of political interference on tertiary institutions such as; recruitment of unqualified personnel, admission of less qualified candidate, internal administration, underdevelopment of tertiary institution, poor quality of tertiary education, poor governance and ineffective leadership, proliferation of tertiary institutions and alteration of planning and location of tertiary institutions across the country. Based on these discoveries, the paper suggested that the federal and state government should grant full autonomy to all tertiary institutions to allow the institutions operate independently.

Event-triggered robot self-assessment to aid in autonomy adjustment.

Introduction: Human-robot teams are being called upon to accomplish increasingly complex tasks. During execution, the robot may operate at different levels of autonomy (LOAs), ranging from full robotic autonomy to full human control. For any number of reasons, such as changes in the robot's surroundings due to the complexities of operating in dynamic and uncertain environments, degradation and damage to the robot platform, or changes in tasking, adjusting the LOA during operations may be necessary to achieve desired mission outcomes. Thus, a critical challenge is understanding when and how the autonomy should be adjusted. Methods: We frame this problem with respect to the robot's capabilities and limitations, known as robot competency. With this framing, a robot could be granted a level of autonomy in line with its ability to operate with a high degree of competence. First, we propose a Model Quality Assessment metric, which indicates how (un)expected an autonomous robot's observations are compared to its model predictions. Next, we present an Event-Triggered Generalized Outcome Assessment (ET-GOA) algorithm that uses changes in the Model Quality Assessment above a threshold to selectively execute and report a high-level assessment of the robot's competency. We validated the Model Quality Assessment metric and the ET-GOA algorithm in both simulated and live robot navigation scenarios. Results: Our experiments found that the Model Quality Assessment was able to respond to unexpected observations. Additionally, our validation of the full ET-GOA algorithm explored how the computational cost and accuracy of the algorithm was impacted across several Model Quality triggering thresholds and with differing amounts of state perturbations. Discussion: Our experimental results combined with a human-in-the-loop demonstration show that Event-Triggered Generalized Outcome Assessment algorithm can facilitate informed autonomy-adjustment decisions based on a robot's task competency.

Using Model Cards for ethical reflection on machine learning models: an interview-based study

How do tools designed for documenting machine learning models contribute to developers’ ethical reflection? We set out to answer this question regarding Model Cards, a tool proposed for such purpose. We conducted a thematic analysis of eight semi-structured interviews based on speculative design sessions. Each participant assumed the role of developer of an artificial intelligence model in one of two scenarios: loan applications or university admissions. We found evidence that designers may have been selective about which ethical issues – from among those they had reflected on – they recorded in the Model Cards. While participants were hesitant to grant full autonomy to the artifact to be developed, we identified they still tended to rely on a third party (outside the design team) to mediate the relationship between the system and other stakeholders. Our findings contribute to our understanding of documentation tools, their epistemic value, and how they can be leveraged to engage in a more ethically informed design process of artificial intelligence systems.

Fiscal federalism and foreign direct investment – An empirical analysis

AbstractPrevious empirical studies suggest that fiscal decentralisation, measured by the number of government layers, is associated with less foreign direct investment (FDI). With an improved dataset on the tax autonomy of sub‐federal government tiers, we present evidence that fiscal decentralisation (de facto) does not reduce FDI. If local governments can set their tax rates and bases autonomously, they attract more FDI. Analysing 128,425 corporate cross‐border acquisitions (CBA), between 194 source and 215 host jurisdictions from 1997 to 2021, we find that full taxation autonomy by subnational governments can double the number of CBAs in a given year. These results apply to high‐income hosts and do not depend on specific periods.

Medical residency in Portugal: a cross-sectional study on the working conditions.

The current European crisis in human resources in health has opened the debate about working conditions and fair wages. This is the case with Resident doctors, which have faced challenges throughout Europe. In Portugal, they account for about a third of the doctors in the Portuguese National Health Service. No studies to date objectively demonstrate the working conditions and responsibilities undertaken. This study aims to quantify the residents' workload and working conditions. Observational, retrospective cross-sectional study which involved a survey on the clinical and training activity of Portuguese residents, actively working in September 2020. The survey was distributed through e-mail to residents' representatives and directly to those affiliated with the Independent Union of Portuguese Doctors. The descriptive analysis assessed current workload, and logistic regression models analyzed associations with geographical location and residency seniority. There were a total of 2,012 participants (19.6% of invited residents). Of the residents giving consultations, 85.3% do so with full autonomy. In the emergency department, 32.1% of the residents work 24 h shifts and 25.1% work shifts without a specialist doctor present. Regarding medical training, 40.8% invest over EUR 1,500 annually. Autonomy in consultations was associated with being a Family Medicine resident (OR 4.219, p < 0.001), being a senior resident (OR 5.143, p < 0.001), and working in the Center (OR 1.685, p = 0.009) and South regions (OR 2.172, p < 0.001). Seniority was also associated with investing over EUR 1,500 in training annually (OR 1.235, p = 0.021). Residents work far more than the contracted 40 h week, often on an unpaid basis. They present a high degree of autonomy in their practice, make a very significant personal and financial investment in medical training, with almost no time dedicated to studying during working hours. There is a need to provide better working conditions for health professionals, including residents, for the sake of the sustainability of health systems across Europe.

Managing Transitions to Autonomous and Electric Vehicles: Scientometric and Bibliometric Review

This paper presents a scientometric and bibliometric literature review of the research on transitions to autonomous and electric vehicles. We discuss the main characteristics, evolution, and various transitional issues, identifying potential trends for future research. The Scopus and WoS search for relevant research articles generated a corpus of 4693 articles, which we analyzed using VOSviewer visualization software. This result shows that the transition research is interdisciplinary, with 54 scientific areas identified. Analysis requires an understanding of the broader aspects of the automotive industry, trends related to sustainability, environment protection, road safety, public policies, market factors and other business, and legal and management issues. This study highlights the need for more research to address the challenges of this global transition in the automotive industry. Topics for future research are constant improvements in AI algorithms used in AVs, innovations in green energy sources, and storage solutions for EVs. This is leading to new innovative business models and platforms. Further to that, the conclusion is that the impact of the transition to a shared economy, the emergency of mobility as a service, and public acceptance of the technology have to be comprehensively considered. The vehicle of the future is seen as a smart electric car, running on green energy, and utilizing various levels of automation up to full autonomy.

A fast planning approach for 3D short trajectory with a parallel framework

For real applications of unmanned aerial vehicles, the capability of navigating with full autonomy in unknown environments is a crucial requirement. However, planning a shorter path with less computing time is contradictory. To address this problem, we present a framework with the map planner and point cloud planner running in parallel in this paper. The map planner determines the initial path using the improved jump point search method on the 2D map, and then it tries to optimize the path by considering a possible shorter 3D path. The point cloud planner is executed at a high frequency to generate the motion primitives. It makes the drone follow the solved path and avoid the suddenly appearing obstacles nearby. Thus, vehicles can achieve a short trajectory while reacting quickly to the intruding obstacles.We demonstrate fully autonomous quadrotor flight tests in unknown and complex environments with static and dynamic obstacles to validate the proposed method. In simulation and hardware experiments, the proposed framework shows satisfactorily comprehensive performance.

Undue Burden the Medical School Application Process Places on Low-Income Latinos

Undue Burden the Medical School Application Process Places on Low-Income Latinos

A collective autoethnography of coproduction in mental health research by academic researchers and young people in Brazil

IntroductionCoproduction of mental health research and interventions involving researchers and young people is increasingly common. However, this model raises challenges, related, for instance, to communication, power and control. This paper...

Evaluating Stage Motion for Automated Electron Microscopy.

Precise control is an essential and elusive quality of emerging self-driving transmission electron microscopes (TEMs). It is widely understood these instruments must be capable of performing rapid, high-volume, and arbitrary movements for practical self-driving operation. However, stage movements are difficult to automate at scale, owing to mechanical instability, hysteresis, and thermal drift. Such difficulties pose major barriers to artificial intelligence-directed microscope designs that require repeatable, precise movements. To guide design of emerging instruments, it is necessary to understand the behavior of existing mechanisms to identify rate limiting steps for full autonomy. Here, we describe a general framework to evaluate stage motion in any TEM. We define metrics to evaluate stage degrees of freedom, propose solutions to improve performance, and comment on fundamental limits to automated experimentation using present hardware.

Vehicle Detection and Tracking with Roadside LiDAR Using Improved ResNet18 and the Hungarian Algorithm.

By the end of the 2020s, full autonomy in autonomous driving may become commercially viable in certain regions. However, achieving Level 5 autonomy requires crucial collaborations between vehicles and infrastructure, necessitating high-speed data processing and low-latency capabilities. This paper introduces a vehicle tracking algorithm based on roadside LiDAR (light detection and ranging) infrastructure to reduce the latency to 100 ms without compromising the detection accuracy. We first develop a vehicle detection architecture based on ResNet18 that can more effectively detect vehicles at a full frame rate by improving the BEV mapping and the loss function of the optimizer. Then, we propose a new three-stage vehicle tracking algorithm. This algorithm enhances the Hungarian algorithm to better match objects detected in consecutive frames, while time-space logicality and trajectory similarity are proposed to address the short-term occlusion problem. Finally, the system is tested on static scenes in the KITTI dataset and the MATLAB/Simulink simulation dataset. The results show that the proposed framework outperforms other methods, with F1-scores of 96.97% and 98.58% for vehicle detection for the KITTI and MATLAB/Simulink datasets, respectively. For vehicle tracking, the MOTA are 88.12% and 90.56%, and the ID-F1 are 95.16% and 96.43%, which are better optimized than the traditional Hungarian algorithm. In particular, it has a significant improvement in calculation speed, which is important for real-time transportation applications.

Hong Kong as a separate customs territory: Past, present and prospect

This article reviews the journey of Hong Kong attaining and retaining the General Agreement on Tariffs and Trade (GATT) and the World Trade Organization (WTO) membership as a separate customs territory, and examines the present challenges for the Hong Kong Special Administrative Region (HKSAR) to maintain its status within the multilateral trade system. By exploring the related facts and laws, the article concludes that Hong Kong has been a separate customs territory member of the GATT and WTO by virtue of the multilateral trade rules, and other countries are not entitled to revoke the HKSAR's separate customs territory status through unilateral measures. Given the past journey and present challenges with the separate customs territory status of Hong Kong, the following prospects can be drawn. The HKSAR remains qualified to possess full autonomy when conducting external commercial relations. A malfunctioning Appellate Body of the Dispute Settlement Body (DSB) may be incapable to safeguard the interests of HKSAR as a separate customs territory.

Opportunistic navigation applied to integration of alternative positioning and electronic mapping based on spline technology

The problem of vulnerability and local incapacity of global satellite navigation systems is formulated. The expediency of alternative positioning methods to create a precedent for high-precision location determination in the satellitedenied environment is revealed. The hypothesis about the impossibility of a separate alternative to meet the requirements of full autonomy of modern navigation when it is necessary to comprehensively solve geolocation scenarios based on the combinatorics of various technologies is put forward. An assumption about the probable advantage of combining data from several information sources to compensate for the disadvantages of each option when predicting an increase in the overall reliability and accuracy of navigation parameters is made. An opportunistic navigation paradigm with the objective function of obtaining location information from mixing additional radio frequency signals with simultaneous visualization of a spline positioning map to determine the location inside a graphic fragment is proposed. The confidence that the approach from the standpoint of spline functions expands the horizon of possibilities of the concept of opportunistic navigation from the purely technical synergetics of the landscape of «signals of opportunity» to the creation of a perspective positioning system using effective electronic mapping is expressed. It is determined that the positioning accuracy of navigation systems is practically necessary to build an optimal trajectory for the safe routing of the vessel. Attention is focused on understanding the optimality of the trajectory as a multi-way planning strategy within the framework of the «receding horizon» paradigm with the obligatory condition that a waypoint with a user-defined probability is achievable by a moving object. It is noted that the modeling of optimal trajectories is implemented by a method similar to the technology of interpolation of navigation contours based on the composition of a B-spline with the provision of an attribute parameter to maintain the same value at each point as a result of the analysis of the spatial anisotropy of the source data. The synthesis of threedimensional spreading of magnetic map anomalies has been tested to create a mapping standard based on a hybrid approximation algorithm as an implementation of a method for computer rendering a geometric primitive of a function of two variables. The postulate of increasing the potential of high-precision localization of the position of any mobile object in space is interpreted, provided that the ontology of opportunistic navigation is applied in practice as the realization of situational awareness of interdependent technical systems in order to maximize the reliability of observation.

Образ женщины в условиях современной псевдодемократической мифологемы

Introduction. The image of a woman helps to construct one’s understanding of the world, relations in society, ideas about the Other. This article is devoted to a critical analysis of the transformation of the image of a woman in a network society. Theoretical analysis. Today, the position of rejecting gender differences, which serve as one of the sources of human culture, is increasing in society. A crisis situation arises, accompanied by the loss of gender self-identification, the violation of internalization and existential frustration. In the network image of society, women are polyvariant and solve it by interpreting the actor who uses it, but a person acquires and manifests his or her generic essence only in the intuitions of the social essence, with the help of transcending. Conclusion. We come to the conclusion that the image of a woman in a network society is constructed by means of a pseudo-democratic mythologeme, which implements the illusion of freedom and leads to the full autonomy of individuals, which is the cause of alienating a person from society and thereby from himself/herself. The proposed way out of the existing gender identity crisis is by means of transcending communication, which includes signification.