A Novel Occupancy Mapping Framework for Risk-Aware Path Planning in Unstructured Environments

In the context of autonomous robots, one of the most important tasks is to prevent potential damage to the robot during navigation. For this purpose, it is often assumed that one must deal with known probabilistic obstacles, then compute the probability of collision with each obstacle. However, in complex scenarios or unstructured environments, it might be difficult to detect such obstacles. In these cases, a metric map is used, where each position stores the information of occupancy. The most common type of metric map is the Bayesian occupancy map. However, this type of map is not well suited for computing risk assessments for continuous paths due to its discrete nature. Hence, we introduce a novel type of map called the Lambda Field, which is specially designed for risk assessment. We first propose a way to compute such a map and the expectation of a generic risk over a path. Then, we demonstrate the benefits of our generic formulation with a use case defining the risk as the expected collision force over a path. Using this risk definition and the Lambda Field, we show that our framework is capable of doing classical path planning while having a physical-based metric. Furthermore, the Lambda Field gives a natural way to deal with unstructured environments, such as tall grass. Where standard environment representations would always generate trajectories going around such obstacles, our framework allows the robot to go through the grass while being aware of the risk taken.

BIG DATA AND DECISION-MAKING SUPPORT

INTRODUCTION: Nowadays, Big Data is created in previously unimaginable quantities. Newly generated data from various Internet of Things (IoT) sensors and their use have never reached their current dimensions. Along with this trend, the availability of devices capable of collecting this data increases, the time for their evaluation is reduced and the volume of data collected at the same time increases. The most important task of research and development in this area is to bring solutions suitable for processing large amounts of data because our current storage and processing capabilities are limited and unable to compete with the storage, processing and publication of the resulting data. OBJECTIVES: Point out the importance of implementing Big Data technology. METHODS: To achieve the goal, the following methodological approach was chosen: study and processing of foreign and domestic literature, acquaintance with similar solutions for data processing, definition of Big Data and IoT, proposal for using Big Data solution to support decision-making, risk definition and evaluation. RESULTS: With the growing amount of disparate and incoherent data and the further growth of the Internet of Things, it is now almost impossible to evaluate all available information correctly and in a timely manner. Without this knowledge, the company loses its competitive advantage and is unable to respond in a timely manner to client requests. CONCLUSION: Implementing a solution for processing Big Data to support decision-making in the company is a complex process. As part of the implementation and use of the Big Data solution to support decision-making, the company must be prepared for the emergence of various problems. We can assume that Big Data technology will constantly be evolving in terms of streamlining analytical tools for obtaining information from large volumes of generated data. Therefore, it is appropriate to create space for the implementation of Big Data technology.

The Relationship between Risk Perception and Risk Definition and Risk-Addressing Behaviour during the Early COVID-19 Stages

The purpose of this article is to show the effect of Risk Perception RP and Risk Definition RD on the Risk-Addressing Behaviour RB. To carry out this study secondary data was used from a semi-structured survey administered between February and June 2020, a period during the early stages of the COVID-19 pandemic. The study identified six dimensions of risk perception and thus tested six structural models. Risk perception (ξ RP) is defined as an external latent variable in the study. It is also assumed that the risk perception variable may affect the risk definition variable (η RD). The application software SmartPLS was used to analyse data through exploratory factor analysis and partial least squares structural equation modelling on our research model. To achieve Convergent validity of the structural equation model of partial least squares, three criteria were met. In the study, Discriminant Validity was examined using the Fornell-Larcker criterion and Heterotrain-Monotrait Ratio (HTMT) coefficients. Results reveal that there is no direct relationship between the RB and “religion and beliefs”, the “fear level, the experience”, the “peer influences level” and the “openness”. However, we found a positive relationship between the agreement on “knowledge” and on RB and statistically significant relationships between the agreement on the RD and the agreement on the “religion and beliefs”, the “fear level”, the “experience”, the “knowledge”, the “peer influences level” and the RB. Moreover, there is an indirect relationship when controlling for the agreement on the RD between the agreement on the RB and the agreement on the “fear level”, the “experience”, the “knowledge” and the “peer influences level”. However, there is no relationship between the agreement on the “openness” and the agreement on the RB and a statistically significant but moderate relationship between the agreement on the RD and the agreement on the RB. Although, there seems to be abundant research on RP, so far we have found only a few studies on the influencing factors of RP, as effected by RB and RD, especially in distressed times such as during this current pandemic period of COVID-19. This study adds to body of literature and sheds new light on the interaction between RP, RB and RD in a time of distress. It provides important and original information that may be useful for government agencies, businesses, individuals, and the media when setting policies, governance structures, regulations, procedures and determining how to communicate.

Risk Assessment for the Selected Surface Water Intake

The purpose of the work is to analyze the risk for surface water intake, taking into account factors affecting the water quality. A three-parameter risk definition was proposed. It was found that the analyzed water intake has an efficient system that protects consumers against drinking water of inadequate quality (multibarier system). The task of the water supply company is to maintain its security measures (including a caution and warning station, biomonitoring) in a state of efficiency.

Exploring the “At-Risk” Student Label Through the Perspectives of Higher Education Professionals

Institutions of higher education often use the term “at-risk” to label undergraduate students who have a higher likelihood of not persisting. However, it is not clear how the use of this label impacts the perspectives of the higher education professionals who serve and support these students. Our qualitative study explores the descriptions and understandings of higher education professionals who serve and support at-risk students. We use thematic analysis (Braun & Clark, 2006) to interpret our data and develop our themes. These themes include conflicting views of the “at-risk” definition, attempts to normalize at-risk, fostering relationships, and “at-promise.”