Computational Intelligence Approaches to Robotics, Automation, and Control
1University of Glasgow, Glasgow, UK
2The University of Auckland, New Zealand
3University of Essex, UK
4Sun Yat-sen University, China
Computational Intelligence Approaches to Robotics, Automation, and Control
Description
Computational Intelligence (CI) approaches are nature-inspired methods, which offer a wealth of ideas for complex problems solving. Compared with the traditional approaches, the CI approaches are more powerful so that they do not need the reformulation of the problem to search a nonlinear and a nondifferentiable space with real world conditions and need for massive parallelism. Another advantage of the CI is the flexibility of the fitness function formulation, which can be expressed as a proper function of the system’s output and suitable for multiobjective (MO) problems. Robotics is a wide range research which includes design, construction, operation, and applications of robots, as well as computer systems for control, sensory feedback, and information processing, in which CI approaches have been widely employed in automation and control that can take the place of humans in dangerous environments or manufacturing processes or resemble humans in appearance, behaviors, and cognition.
The special issue will include theoretical, numerical, and experimental contributions that describe original research results and innovative concepts that address all aspects of robotics and CI approaches and are applying their results in the context of robotics, automation, and control. The aim would be to establish a common understanding about the state of the field, draw a road map on where the research is heading, highlight the issues, and discuss the possible solutions. It is also available to concerned review/regular articles that will support and stimulate the continuing efforts to understand the research and development of CI approaches for optimizations and field applications. Potential topics include, but are not limited to:
- Kinematics, dynamics, control, and simulation of robots
- MO problems in robotics
- Human-machine interface and integration
- Robotics-related computer hardware, software, and architectures
- Robotics in manufacturing and flexible automation
- Distributed and parallel MO for robotics
- Hybrid MO methodologies for robotics
- Performance metrics or preference articulation in MO for robotics
- Uncertainty handling for robotics
- Field applications: unmanned aerial vehicle (UAV), autonomous underwater vehicle (AUV), humanoids, and so forth
- Computer vision and robotics
- Assistive technology, rehabilitation, and musculoskeletal biomechanics
- Big data and robotics
- Evolutionary robotics
Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/mpe/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/mpe/ciar/ according to the following timetable: