Mobile Intelligent Autonomous Systems

Mobile intelligent autonomous systems (MIAS) is a fast emerging research area. Although it can be regarded as a general R&D area, it is mainly directed towards robotics. Several important subtopics within MIAS research are:(i) perception and reasoning, (ii) mobility and navigation,(iii) haptics and teleoperation, (iv) image fusion/computervision, (v) modelling of manipulators, (vi) hardware/software architectures for planning and behaviour learning leadingto robotic architecture, (vii) vehicle-robot path and motionplanning/control, (viii) human-machine interfaces for interaction between humans and robots, and (ix) application of artificial neural networks (ANNs), fuzzy logic/systems (FLS),probabilistic/approximate reasoning (PAR), Bayesian networks(BN) and genetic algorithms (GA) to the above-mentioned problems. Also, multi-sensor data fusion (MSDF) playsvery crucial role at many levels of the data fusion process:(i) kinematic fusion (position/bearing tracking), (ii) imagefusion (for scene recognition), (iii) information fusion (forbuilding world models), and (iv) decision fusion (for tracking,control actions). The MIAS as a technology is useful for automation of complex tasks, surveillance in a hazardousand hostile environment, human-assistance in very difficultmanual works, medical robotics, hospital systems, autodiagnosticsystems, and many other related civil and military systems. Also, other important research areas for MIAScomprise sensor/actuator modelling, failure management/reconfiguration, scene understanding, knowledge representation, learning and decision-making. Examples ofdynamic systems considered within the MIAS would be:autonomous systems (unmanned ground vehicles, unmannedaerial vehicles, micro/mini air vehicles, and autonomousunder water vehicles), mobile/fixed robotic systems, dexterousmanipulator robots, mining robots, surveillance systems,and networked/multi-robot systems, to name a few.Defence Science Journal, 2010, 60(1), pp.3-4, DOI:http://dx.doi.org/10.14429/dsj.60.9

Sensing and connection systems for assisted and autonomous driving and unmanned vehicles

The special issue, “Sensors, Wireless Connectivity and Systems for Autonomous Vehicles and Smart Mobility” on MDPI Sensors presents 12 accepted papers, with authors from North America, Asia, Europe and Australia, related to the emerging trends in sensing and navigation systems (i.e., sensors plus related signal processing and understanding techniques in multi-agent and cooperating scenarios) for autonomous vehicles, including also unmanned aerial and underwater ones

The concept of collaborative engineering: a systematic literature review

Collaborative engineering is not a new subject but it assumes a new importance in the Industry 4.0 (I4.0). There are other concepts frequently mismatched with collaboration. Thus, the main objective of this paper is to put forward a collaborative engineering concept, along its sub concepts, supported by an extensive systematic literature review. A critical analysis and discussion about the fundamental importance of learning, and the central human role in collaboration, in the I4.0, is presented, based on the main insights brought through the literature review. This study also enables to realize about the importance of collaboration in the current digitalization era, along with the importance of recent approaches and technology for enabling or promoting collaboration. Main current practices of human centered and autonomous machine-machine approaches and applications of collaboration in engineering, namely in manufacturing and management, are presented, along with main difficulties and further open research opportunities on collaboration.This work was supported by the Fundação para a Ciência e a Tecnologia [UIDB/00319/2020, UIDB/50014/2020, and EXPL/EME-SIS/1224/2021]