IEEE Robotics and Automation Society IEEE

Special Issue on Emerging Advances and Applications in Automation

Contributions are solicited on state-of-the-art research and applications in the general area of automation, and, according to the nature of IEEE RAM, having solid and significant industrial and practical impacts. The goal is to bring together researchers and practitioners from both academia and industry, to present efficient scientific and engineering solutions, address the needs and challenges for integration with new technologies, and provide visions for future research and development. The issue will feature original, significant and visionary automation papers describing scientific methods and technologies with both solid theoretical development and practical importance. Papers that describe innovative work on abstractions, algorithms, theories, methodologies, models, systems, and case studies that can be applied across industries to significantly advance efficiency, quality, productivity, and reliability for society are welcome. In addition, participation from industry practitioners interested in integrating knowledge across disciplines is encouraged.

The topics include but are not limited to:

• Foundations of Automation;
• Automation in Life Sciences and Health Care;
• Automation in Meso, Micro and Nano-scale;
• Manufacturing Automation;
• Discrete Event Systems;
• Mechatronics;
• Sustainable Production;
• Logistics and Supply Chain Management;
• Smart Buildings and Smart Cities;
• Emerging Topics in Automation.

RAM also considers multimedia material (typically, videos) accompanying the submission of a paper. Instructions on the preparation of this material can be found on Multimedia will appear side-by-side to the accepted paper in the electronic version of the Special Issue within IEEE Xplore.


Call for papers - March 2014
Deadline for paper submission - 20 June 2014
First review - 15 September 2014
Final review - 15 November 2014
Publication - March 2015

Guest Editors:

Maria Fanti Politecnico di Bari, Dipartimento di Elettrotecnica ed Elettronica, Bari, Italy. This email address is being protected from spambots. You need JavaScript enabled to view it.
Ken Goldberg University of California-Berkeley, IEOR and EECS School of Information. Berkeley California, United States. This email address is being protected from spambots. You need JavaScript enabled to view it.
Youfu Li IEEE Senior Member, Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Kowloon, HK. This email address is being protected from spambots. You need JavaScript enabled to view it.,
Yu Sun University of Toronto, Department of Mechanical and Industrial Engineering, Department of Electrical and Computer Engineering, Institute of Biomedical Engineering, Ontario (ON), Canada. This email address is being protected from spambots. You need JavaScript enabled to view it.

Special Issue on Wearable Robotics

Deadline for Paper Submission: 10 March 2014
First Review: 31 May 2014
Final Review: 1 September 2014
Publication Schedule: December 2014

A Wearable Robot (WR) is an artificial apparatus that is placed in a close fit to the human’s body, thereby moving and working in synchrony with its limbs. Examples of WRs include active exoskeletons, which are worn in parallel to the user’s body so as to augment its performance, and active limb-prostheses, which are worn in series to the user’s body so as to replace some missing extremity. WRs make it possible to realize a human-robot symbiotic system with enhanced/restored strength, speed, endurance and energetic autonomy. Practical applications of WRs range from physical assistance of the elderly, disabled people and heavy duty workers to the functional rehabilitation and restoration of lost functions. 

Since the last decade, significant advances have occurred in Wearable Robotics, which is now attracting the interest from the industry and the media. However, the development of a complete and functional WR is still a very challenging task, which deserves innovations under several regards, including ergonomics, kinematics, dynamics, actuation, interaction control and energetics. In this context, this special issue focuses on complete and working Wearable Robots, and specifically targets at presenting new scientific results and methodologies that can assist the practicing engineer in the design, development, control and validation of novel WR systems. 

Scope, Description and information
Researchers working in Industry and Academia are invited to submit their original and unpublished research results on technological and experimental aspects associated with the design, development, control and validation of complete and working Wearable Robotic systems. 

Topics of interest include: 
• Power extenders for material handling; 
• Robotic orthoses for physical assistance and rehabilitation; 
• Active limb-prostheses; 
• Wearable haptic exoskeletons; 
• Novel design and validation methodologies for wearable robots. 

Guest Editors 
• Rocco Vertechy, PERCRO Lab, Scuola Superiore Sant’Anna, Pisa (Italy)
• Dino Accoto, Biomedical Robotics and Biomicrosystems Lab, University Campus Bio-Medico di Roma, Rome (Italy) 
• Hugh Herr, MIT Media Lab, Massachusetts Institute of Technology, Cambridge (MA, USA)

Special Issue on Emerging Applications of Stochastic Geometry in Autonomous Robotics

A special issue of the IEEE Robotics and Automation Magazine.


The robust interpretation of an autonomous vehicle's environment, as well as its own position in that environment, underlies almost all autonomous robotic applications. This Simultaneous Localization And Map building (SLAM) problem requires a robust representation of the vehicle's surroundings (the map) in the presence of sensing/feature detection uncertainties such as false positives, missed detections and spatial errors. Significant research activity now exists in representing both measurements and the feature based SLAM map as a Random Finite Set (RFS), rather than the conventionally used random vector. This is not merely a triviality of representation. Recent research has shown that Finite Set Statistics (FISST), developed for data fusion and estimation with RFSs, when applied to sensor representations and SLAM, can eliminate the necessity of fragile map management and feature associationalgorithms. Robotic sensing, mapping and SLAM applications which use FISST in the form of the Probability Hypothesis Density (PHD), Cardinalized PHD (C-PHD) and Multi-Target, Multi-Bernoulli (MeMBer) filters have already demonstrated robust means of representing uncertain sensor data and maps, with the unique abilities of jointly tracking both object spatial and existence uncertainties.

The RFS representation of sensor data and robotic maps therefore provides a robust paradigm under which the true number of features, which have entered the field(s) of view of an autonomous vehicle's sensor(s), as well as their locations, can be jointly estimated in a Bayes optimal manner, while taking into account feature detection and false alarm probabilities.

Scope, Description, and More Information

This special issue calls for magazine style articles on the direct application of FISST to the issues of autonomous robotic sensing, mapping and navigation with diverse sensing techniques and in various environments. The robustness of the solutions presented should be demonstrated in the presence of sensing and sensor processing uncertainty. Comparisons with conventional vector based techniques are also encouraged. Topics of interest include, but are not limited to:

  • Use of Sets for Sensor and Map Representations
  • PHD Smoothing and Filtering Applications in Robotics
  • Sensing, Mapping and SLAM in high clutter levels
  • Multi-Vehicle SLAM
  • Jointly incorporating object existence and spatial uncertainties into mapping and SLAM
  • Metrics to determine full mapping and SLAM errors
  • Detecting and Tracking Extended Targets

To submit a paper, go here.

Important Dates

Call for Papers September 24, 2012
Deadline for Paper Submission March 10, 2013
First Review April 10, 2013
Final Review May 10, 2013
Publication June 2014


Guest Editors: Martin Adams, Ba-Ngu Vo and Ronald Mahler

Martin Adams

Martin Adams

Santiago (Region Metropolitana Santiago), Chile 
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Ba-Ngu Vo

Curtin University
Department of Electrical and Computer Engineering
Perth, WA Austrailia
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Ronald P. Mahler

Lockheed Martin Advanced Technology Laboratories
Senior Staff Research Scientist
Eagan, MN USA
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