Past, present and future of path-planning algorithms for mobile robot navigation in dynamic environments

Mobile robots have been making a significant contribution to the advancement of many sectors including automation of mining, space, surveillance, military, health, agriculture and many more. Safe and efficient navigation is a fundamental requirement of mobile robots, thus, the demand for advanced algorithms rapidly increased. Mobile robot navigation encompasses the following four requirements: perception, localization, path-planning and motion control. Among those, path-planning is a vital part of a fast, secure operation. During the last couple of decades, many path-planning algorithms were developed. Despite most of the mobile robot applications being in dynamic environments, the number of algorithms capable of navigating robots in dynamic environments is limited. This paper presents a qualitative comparative study of the up-to-date mobile robot path-planning methods capable of navigating robots in dynamic environments. The paper discusses both classical and heuristic methods including artificial potential field, genetic algorithm, fuzzy logic, neural networks, artificial bee colony, particle swarm optimization, bacterial foraging optimization, ant-colony and Agoraphilic algorithm. The general advantages and disadvantages of each method are discussed. Furthermore, the commonly used state-of-the-art methods are critically analyzed based on six performance criteria: algorithm's ability to navigate in dynamically cluttered areas, moving goal hunting ability, object tracking ability, object path prediction ability, incorporating the obstacle velocity in the decision, validation by simulation and experimentation. This investigation benefits researchers in choosing suitable path-planning methods for different applications as well as identifying gaps in this field. © 2020 IEEE

E-Learning in Industrial Electronics during Covid-19

The educational methodologies employed in Industrial Electronics have been affected by Covid-19. In many cases, conventional learning methods relying on face-to-face lectures have been replaced by online methodologies. The whole process has required a fast adaptation and development of the e-learning tools to ensure a quality of theoretical, practical and laboratory lectures, as well as the development of new methods for the reliable assessment of the learning process. From this perspective, the present paper deals with the different strategies that have been implemented in institutions of several countries located in different geographical areas, including Portugal, Spain, Japan and Australia. It is shown that the use of methodologies, such as flip teaching, has provided a wide variety of possibilities to adapt to the new educational context. Moreover, for Industrial Electronics degrees, the use of virtual or remote laboratories, portable learning tools and advanced information and communication technologies have also risen as valuable resources. The paper also reports the problems arising during the development of the e-learning tools, their implementation constraints, and the evaluation of their results. © 2021 IEEE