Journal Information
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Impact Factor:

Call For Papers
The scope of the IEEE Transactions on Systems, Man, and Cybernetics: Systems includes the fields of systems engineering. It includes issue formulation, analysis and modeling, decision making, and issue interpretation for any of the systems engineering lifecycle phases associated with the definition, development, and deployment of large systems. In addition, it includes systems management, systems engineering processes, and a variety of systems engineering methods such as optimization, modeling and simulation.
Last updated by Dou Sun in 2016-09-25
Special Issues
Special Issue on Autonomous Cognitive Robotics and Systems
Submission Date: 2017-05-31

Cognitive systems are natural (i.e. animal and human) or artificial (such as software and robotic) information processing systems that can perform ???cognitive-like??? functions such as: perception, attention, action, socio-affective and cognitive learning, memory, decisionmaking and control, language processing and communication, reasoning, problem solving and consciousness. Autonomous Cognitive Systems is an emerging discipline, fusing ideas across several traditional fields and seeks to further our understanding in two problem domains. First, by instantiating brain models into a virtual, simulated or embodied form, it supplies a strong test of those models, thereby furthering our understanding of neurobiology and cognitive psychology. Second, by harnessing the insights we have about cognition, it is a potentially fruitful source of engineering solutions to problems in autonomous systems, including those in: robotics, autonomous vehicles, planetary rovers, artificial social companions and assistive technology. It therefore promises next-generation solutions in the design and study of autonomous cognitive robotics and systems, including those organized in teams, swarms or as individual robots or agents, and controlled through varying degrees of human interaction and autonomy. The aim of this exciting Special Issue is to bring together leading scientists, engineers and industry researchers, to submit original pioneering contributions in autonomous cognitive robotics and systems research. Articles will be solicited on theoretical, computational, experimental and integrative aspects of autonomous cognitive systems, or core modules of such systems. Application environments of interest include real-world industrial, indoor, outdoor, everyday life, emergency, hostile and outer space where brain-inspired cognitive technologies are required for autonomous robots and systems to accomplish challenging real-time goals, to at least some degree of self-sufficiency. Timely review papers identifying future R&D challenges and opportunities will also be welcome. Topics of interest: All applied, theoretical, computational, experimental and integrative aspects of autonomous cognitive robotics and systems research, including (but not limited to): - perception - action - socio-affective and cognitive learning and memory - attention - autonomous decision making and control - social cognition - natural language processing and communication, - reasoning - problem solving - consciousness - cognitive system architectures and implementations
Last updated by Dou Sun in 2016-09-25
Special Issue on Intelligent Sensing, Planning and Control for Autonomous Driving Vehicles
Submission Date: 2017-07-31

The IEEE Transactions on Systems, Man, and Cybernetics: Systems calls for research paper submissions for considering in a Special Issue publication featuring on intelligent sensing, planning and control for autonomous driving vehicles. Unpublished original contributions from prospective authors are invited for consideration by the special issue, subject to blind reviews, with main focus on new theory and technologies for improving the performance of autonomous driving vehicles in complex, uncertain environments. Comprehensive case studies and in-depth review papers will also be considered. In the past decades, intelligent vehicles have received increasingly significant attention due to their great potential in enhancing vehicle safety and performance, and traffic efficiency. One of the key objectives of intelligent vehicles is to realize a high degree of autonomy under dynamic, complex environments. From multi-disciplinary perspectives including robotics, computer vision, artificial intelligence, control theory, et al, many research efforts have been devoted to improving the performance of autonomous sensing, planning and control abilities for intelligent vehicles. Furthermore, due to the requirements of unknown complex environments, it is necessary for intelligent vehicles to have improved learning ability such as online learning and driving skill learning from past experiences for sensing, planning and motion control. In real-world traffic, there are various uncertainties and complexities in road and weather conditions, objects and obstacles are dynamic, as is the interaction between the tires and the driving terrain, etc. An autonomous vehicle has to deal with the following technical challenges: (i) to rapidly and accurately detect, recognize and track dynamic objects with complex backgrounds, (ii) to build accurate maps and realize self-localization in uncertain, dynamic environments, (iii) to implement motion planning and avoid dynamic obstacles with multiple goals such as safety, agility, and traffic efficiency, and (iv) to learn from past experience and reuse the learned knowledge to continually improve driving performance. This special issue seeks to explore the areas related to these challenges.
Last updated by Dou Sun in 2017-01-19
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