Realtime autonomous navigation in V-Rep based static and dynamic environment using EKF-SLAM

<p>Localization in an autonomous mobile robot allows it to operate autonomously in an unknown and unpredictable environment with the ability to determine its position and heading. Simultaneous localization and mapping (SLAM) are introduced to solve the problem where no prior information about the environment is available either static or dynamic to achieve standard map-based localization. The primary focus of this research is autonomous mobile robot navigation using the extended Kalman filter (EKF)-SLAM environment modeling technique which provides higher accuracy and reliability in mobile robot localization and mapping results. In this paper, EKF-SLAM performance is verified by simulations performed in a static and dynamic environment designed in V-REP i.e., 3D Robot simulation environment. In this work SLAM problem of two-wheeled differential drive robot i.e., Pioneer 3-DX in indoor static and dynamic environment integrated with Laser range finder i.e., Hokuyo URG-04LX- UG01, LIDAR, and Ultrasonic sensors is solved. EKF-SLAM scripts are developed using MATLAB that is linked to V-REP via remote API feature to evaluate EKF-SLAM performance. The reached results confirm the EKF- SLAM is a reliable approach for real-time autonomous navigation for mobile robots in comparison to other techniques.</p>

APPLICATION OF BRANCHES IN MICROSOFT FORMS DOCUMENTS AS FORCED REPLACEMENT OF SIMULATION PRACTICAL-ORIENTED TASKS, WHILE STUDYING CLINICAL DISCIPLINES IN THE CONDITIONS OF THE CONTINUING COVID-19 PANDEMIC

Sorry to state that optimistic forecasts for a quick overcoming of the COVID-19 pandemic, unfortunately, did not come true. Accepting modern challenges, the higher education sector, like other areas of human life, continues to adapt and optimize work to the new conditions of a changing difficult, unpredictable environment. While theoretical medical disciplines are likely to experience this re-equipment with greater ease, practice-oriented subjects are in a situation of crisis in the quality of vocational education. Results. In such circumstances, simulation systems, which are designed to create a safe environment, where, without risks to the patient, the future specialist can work out typical clinical situations, can be useful. Creating the comprehensive models requires considerable effort and highly specialized knowledge of working with specific software. However, if your aim is to create short cases that can be directly integrated in the form of multiple learning tasks to Microsoft Teams - you should pay attention to the well-known Forms tool from the Office365 cloud service package, which is available by subscription in many schools of this country. On purpose of such task formation, we will be able to create branches, providing the use of optional choice questions. When using this function, we get the opportunity to redirect the respondent to different fragments of the form, depending on the chosen answer. Wrong options should be left as well among the proposed, but at the end a result of their choice brief comments, should be made, explaining their absurdity, which would be available for review in case of completion of the task with an erroneous result. The result of such work will be a tree of steps, each of which brings the respondent closer to the case designed by the architect. Based on a system of diagnostic and treatment protocols, it is possible to calculate and formulate algorithms of action in certain clinical circumstances and, finally, create a Microsoft Forms document. This form, provided a combination of text and graphic data, allows you to place the respondent in a professional situation easily. Such system gives the opportunity to make typical correct decisions or to make wrong steps, which brings to the circumstances an element of simulation training. Thanks to the built-in assessment system, it is possible to combine learning processes with ongoing and final monitoring of the quality of learning, to stimulate maximizing the result. Upon reaching a positive outcome, form an opinion about the assimilation of the element, or redirect to additional study of certain fragments of topics, in case of formation of the wrong network of steps. To simplify learning, some cases can be prepared with one pass option, which will allow you to practice skills of emergency situations, or tasks limited to a standardized step-by-step solution. Conclusions. The Microsoft Forms cloud application can be used to create short clinical cases. Requires a combination of different types of input data and the ability to create branches to use it as a simulation learning tool. As a result, a decision tree is formed, which can be focused on assessing the acquisition of skills, and used to grade respondents, or to develop standardized solutions in typical clinical situations. The outlined system has its drawbacks, but it is necessary to take into account the general availability and ease of configuration.

Reactive Planning-Driven Approach to Online UAVs Mission Rerouting and Rescheduling

The presented problem concerns the route planning of a UAV fleet carrying out deliveries to spatially dispersed customers in a highly dynamic and unpredictable environment within a specified timeframe. The developed model allows for predictive (i.e., taking into account forecasted changing weather conditions) and reactive (i.e., enabling contingency UAVs rerouting) delivery mission planning (i.e., NP-hard problem) in terms of the constraint satisfaction problem. Due to the need to implement an emergency return of the UAV to the base or handling ad hoc ordered deliveries, sufficient conditions have been developed. Checking that these conditions are met allows cases to be eliminated if they do not guarantee acceptable solutions, thereby allowing the calculations to be sped up. The experiments carried out showed the usefulness of the proposed approach in DSS-based contingency planning of the UAVs’ mission performed in a dynamic environment.

Attention U-Net with Feature Fusion Module for Robust Defect Detection

U-Net shows a remarkable performance and makes significant progress for segmentation task in medical images. Despite the outstanding achievements, the common case of defect detection in industrial scenes is still a challenging task, due to the noisy background, unpredictable environment, varying shapes and sizes of the defects. Traditional U-Net may not be suitable for low-quality images with low illumination and corruption, which are often presented in the practical collections in real-world scenes. In this paper, we propose an attention U-Net with feature fusion module for combining multi-scale features to detect the defects in noisy images automatically. Feature fusion module contains convolution kernels of different scales to capture shallow layer features and combine them with the high-dimensional features. Meanwhile, attention gates are used to enhance the robustness of skip connection between the feature maps. The proposed method is evaluated on two datasets. The best precision rate and MIoU of defect detection are 95.6% and 92.5%. The best F-score of concrete crack detection is 95.0%. Experimental results show that the proposed approach achieves promising results in both datasets. It demonstrates that our approach consistently outperforms other U-Net-based approaches for defect detection in low-quality images. Experimental results have shown the possibility of developing a mixture system that can be deployed in many applications, such as remote sensing image analysis, earthquake disaster situation assessment, and so on.

Reactive UAV Fleet’s Mission Planning in Highly Dynamic and Unpredictable Environments

Unmanned aerial vehicles (UAVs) create an interesting alternative for establishing more sustainable urban freight deliveries. The substitution of traditional trucks in the last-mile distribution by a UAV fleet can contribute to urban sustainability by reducing air pollution and increasing urban freight efficiency. This paper presents a novel approach to the joint proactive and reactive planning of deliveries by a UAV fleet. We develop a receding horizon-based approach to reactive, online planning for the UAV fleet’s mission. We considered the delivery of goods to spatially dispersed customers over an assumed time horizon. Forecasted weather changes affect the energy consumption of UAVs and limit their range. Therefore, consideration should be given to plans for follow-up tasks, previously unmet needs, and predictions of disturbances over a moving time horizon. We propose a set of reaction rules that can be encountered during delivery in a highly dynamic and unpredictable environment. We implement a constraint programming paradigm, which is well suited to cope with the nonlinearity of the system’s characteristics. The proposed approach to online reactive UAV routing is evaluated in several instances. The computational experiments have shown that the developed model is capable of providing feasible plans for a UAV fleet’s mission that are robust to changes in weather and customer’s orders.

About some trends in the development of agricultural cooperatives in Canada

The article presents the results of the analysis and generalization of the experience of the development of agricultural cooperatives in Canada (a country with a centuries-old history of agricultural cooperation), its successful cooperative practices at various historical stages (including the present). Within the framework of the presented study, a number of important scientific conclusions were obtained, including: 1) generalization of trends in the evolution of Canadian farms (as active participants in agricultural cooperation) and characteristics of their current state; 2) specification of technological and organizational innovations undertaken by Canadian agricultural cooperatives to strengthen their competitive position; 3) identification of promising trends in the development of agricultural cooperation in Canada, reflecting both the essential transformations of the phenomenon under consideration (agricultural cooperative), and fluctuations of its environment; 4) determining the importance of using foreign (Canadian) cooperative experience for the development of agricultural cooperation in Russia. The presented material is distinguished by the novelty of approaches, the adequacy of the research tools used, and the representativeness of the statistical data used. The factors of the effective functioning of Canadian agricultural cooperatives scientifi cally substantiated in the study, as well as the basic principles of their modern models, are advisable to use (as international experience) in the development of the domestic system of agricultural cooperation in a modern (global, mobile, unstable, unpredictable) environment, taking into account its new challenges. The conclusions obtained in the course of the work and the conclusions proposed by the authors are of both scientific interest (for further theoretical and empirical research) and practical significance (for specialists interested in the creation and successful functioning of domestic agricultural cooperatives).

A Construction of Entrepreneurial Personality Tests: Testing Archetype Personality Inventory in Entrepreneurship

VUCA is about a hyper-competitive and unpredictable environment. It stands for volatility, uncertainty, complexity, and ambiguity. Personal attributes are necessary to navigate the VUCA environment. Studies in entrepreneurship show that narratives help people to connect different experiences. Literature shows that a narrative journey can be described through archetypes and relate to entrepreneurial behavior. This study aims to construct and validate measurements of entrepreneurial personality by adapting Pearson & Marr's archetype inventory test within the entrepreneurial context. This study was conducted as an assessment of the measurement psychometric attributes consisting of 12 archetypes. Explanatory Factor Analysis (EFA) was carried out by Oblimin rotation resulting in 60 final items. This study involved 154 small and medium entrepreneurs in Jakarta and West Java.

Simultaneous task placement and sequence optimization in an inspection robotic cell

In this article, we improve the efficiency of a turbine blade inspection robotic workcell. The workcell consists of a stationary camera and a 6-axis serial robot that is holding a blade and presenting different zones of the blade to the camera for inspection. The problem at hand consists of a 6-DOF (degree of freedom) continuous optimization of the camera placement and a discrete combinatorial optimization of the sequence of inspection poses (images). For each image, all robot configurations (up to eight) are taken into consideration. A novel combined approach is introduced, called blind dynamic particle swarm optimization (BD-PSO), to simultaneously obtain the optimal design for both domains. The objective is to minimize the cycle time of the inspection process, while avoiding any collisions. Even though PSO is vastly used in engineering problems, the novelty of our combinatorial optimization method is in its ability to be used efficiently in traveling salesman problems where the distances between the cities are unknown and subject to change. This highly unpredictable environment is the case of the inspection cell where the cycle time between two images will change for different camera placements.

Prenatal environmental variation, alternative reproductive tactics and the formation of a mixed-kin cooperative society

Although animal societies often evolve due to limited natal dispersal that results in kin clustering and facilitates cooperation among relatives, many species form cooperative groups with low and variable kin structure. To understand how such mixed-kin societies form despite their potential for social conflict, we investigated the environmental causes and subsequent fitness consequences of dispersal decisions in male cooperatively breeding superb starlings (Lamprotornis superbus) living in a climatically unpredictable environment. We show that the two alternative reproductive tactics—natal dispersal vs. philopatry—exhibit reproductive tradeoffs resulting in equal lifetime inclusive fitness. The tactic an individual adopts is governed by the environment its parents experience prior to laying rather than the environment it experiences as an adolescent. When individuals adopt the tactic not predicted by early life environmental conditions, their fitness is reduced. Ultimately, climate-driven oscillating selection may help stabilize mixed-kin animal societies by influencing alternative reproductive trajectories early in life.