journal: Paladyn, Journal of Behavioral Robotics

Open Access Published since March 1, 2010

Paladyn, Journal of Behavioral Robotics

ISSN: 2081-4836

Editors-in-chief: Adrian D. Cheok, Gregor Schöner

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About this journal

Topical/Special Issues:

Robotics in Education
Submission deadline: October 1st, 2023
Humanoid Robots and Human-Robot Interaction in the Age of 5G and Beyond
Submission deadline: September 1st, 2023
Nikola Tesla’s Inventions in the Field of Intelligent Robotics in collaboration with EAI International Conference on Advances in Nikola Tesla Technologies in the Twenty First Century
Submission deadline: September 30th, 2023

Recent Advancements in the Role of Robotics in Smart Industries and Manufacturing Units
Submission deadline: June 30th, 2023

For past special issues please visit the website.

AIM AND SCOPE

Paladyn, Journal of Behavioral Robotics is a fully peer-reviewed, open access, electronic-only journal that publishes original, high-quality research on topics broadly related to neuronally and psychologically inspired robots and other behaving autonomous systems. The journal provides the readers with free, instant, and permanent access to all content worldwide; and the authors with extensive promotion of published articles, long-term preservation, no space constraints, and quick publication upon the acceptance.

Paladyn, Journal of Behavioral Robotics is indexed by SCOPUS. Our standard policy requires each paper to be reviewed by at least two Referees and the peer-review process is single-blind.

The aim of Paladyn is to become a premier source of knowledge and a worldwide-recognized platform of exchange for scientists of different disciplinary origins and backgrounds (e.g., engineers, computer scientists, physicists, neuroscientists, psychologists, sociologists) who are inspired by the analogy between robotic autonomy and human behaviour.

Topics

human-robot interaction
cognitive robotics
developmental robotics
affective robotics
evolutionary robotics, genetic algorithms
artificial life, artificial intelligence
assistance robotics
visual cognition, computer vision
neurally inspired robotics, animats
neural networks, neural computation
humanoid

Your Benefits

Why subscribe and read

Paladyn, Journal of Behavioral Robotics is a premier source of a high quality research of interdisciplinary character – of interest to a broad range of researchers working in different disciplines. All published articles are made freely and permanently accessible online.

Authors benefit from:

constructive peer-review
no space constraints
no submission charge; article processing charge - discount or free publication in case the authors have limited funds
quick online publication of accepted papers*
Open Access for all articles**
promotion of published papers to readers and citers
liberal policies on copyrights (authors retain copyrights) and on self-archiving (no embargo periods)
long-term preservation of the content***

* The journal uses continuous publication model - accepted manuscripts are published quickly after the acceptance.
** Thanks to Open Access, all articles are freely available to the academic community worldwide without any restrictions, there are more liberal policies on copyrights (authors retain copyright) and on self-archiving (no embargo periods).
*** The journal is archived in Portico.

Detailed information on Editorial Policy, Publication Ethics, Instructions for Authors etc. can be found in the Supplementary Materials section.

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Supplementary Materials

Topics

External Links

Volume 14 Issue 1

January 2023

Regular Article

Open Access February 1, 2023

The role of prior exposure in the likelihood of adopting the Intentional Stance toward a humanoid robot

Cecilia Roselli, Serena Marchesi, Davide De Tommaso, Agnieszka Wykowska

Article number: 20220103

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Abstract

One of the key questions in human–robot interaction research is whether humans perceive robots as intentional agents, or rather only as mindless machines. Research has shown that, in some contexts, people do perceive robots as intentional agents. However, the role of prior exposure to robots as a factor potentially playing a role in the attribution of intentionality is still poorly understood. To this end, we asked two samples of high school students, which differed with respect to the type of education they were pursuing (scientific/technical vs. artistic) to complete the InStance Test, measuring individual tendency to attribute intentionality toward robots. Results showed that, overall, participants were more prone to attribute intentionality to robots after being exposed to a theoretical lecture about robots’ functionality and use. Moreover, participants’ scientific/technical education resulted in a higher likelihood of attribution of intentionality to robots, relative to those with artistic education. Therefore, we suggest that the type of education, as well as individually acquired knowledge, modulates the likelihood of attributing intentionality toward robots.

Review Articles

Open Access February 2, 2023

Robot-assisted therapy for upper limb impairments in cerebral palsy: A scoping review and suggestions for future research

Melanie Jouaiti, Kerstin Dautenhahn

Article number: 20220104

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Abstract

A growing number of studies investigate the use of robotics therapy for motor (re)habilitation with children with cerebral palsy (CP). Most of these studies use functional robots in very repetitive sessions. While the therapy is effective, very few studies employ social robots, which appears to be a missed opportunity to design more compelling and enjoyable sessions for the children. In this article, we will review robot-assisted upper limb motor (re)habilitation for children with CP. Previous reviews of robot-assisted therapy for CP had mostly focused on lower limbs, or the review was made from a medical point of view, with the sole concern being the therapy’s effectiveness. Here, we focus our review on robot-assisted upper limb (re)habilitation and address human–robot interaction considerations. We searched PubMed, Scopus, and IEEE databases and argue that although this area of research is promising and already effective, it would benefit from the inclusion of social robots for a more engaging and enjoyable experience. We suggest four scenarios that could be developed in this direction. The goal of this article is to highlight the relevance of the past work and encourage the development of new ideas where therapy will socially engage and motivate children.

Open Access April 4, 2023

Is integrating video into tech-based patient education effective for improving medication adherence? – A review

Muhammad Thesa Ghozali

Article number: 20220109

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Abstract

Patient education is a crucial part of the efforts to improve the level of medication adherence. Successful diabetes self-management will be achieved if health practitioners (doctors, pharmacists, nurses, and other health-related professionals) provide education to their patients. One of the multimedia platforms that are now popular in patient education and health promotion is video. This study primarily aimed to review published research examining integration of video-based digital interventions into tech-based patient education methods to promote medication adherence in diabetic patients. All of the articles presented in this review were collected from the PubMed, Science Direct, and Sage Publication databases. This review compared study samples, intervention characteristics (length of intervention and learning media), and adherence outcomes, as well as additional outcomes across the studies. Of the 304 articles reviewed, seven studies that met the criteria were found and included in the review. Overall, 57.14% of the integrated video-based interventions demonstrated improved medication adherence and 42.86% demonstrated improvement in other related health outcomes. The interventions were 7 weeks to 6 months in length and were in the form of storytelling with videos, smartphone apps, educational programs, or web-based education. It can be concluded that video-based digital interventions aimed to improve medication adherence in diabetic patients are promising. For optimum outcomes, this study highly suggests that a combination of video (synchronous and asynchronous) and a good patient education program is an ideal form of intervention for patients with type 2 diabetes. Regarding the education platform, the intervention could be humanoid robots, storytelling, mobile health (mHealth) apps, websites, robot-enhanced diabetes care, and other related tech-based programs or even conventional models.

Special Issue: Recent Advancements in the Role of Robotics in Smart Industries and Manufacturing Units

Open Access February 1, 2023

Adoption of IoT-based healthcare devices: An empirical study of end consumers in an emerging economy

Abhisek Dutta, Raj K. Kovid, Mounika Thatha, Jatin Gupta

Article number: 20220106

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Abstract

The Internet of things (IoT) is a technology with varied applications in numerous fields. One such field is healthcare, which has a dire need of using this technology to help millions benefit from the attention and availability of healthcare professionals. This study identifies important factors that influence the adoption of IoT-based healthcare devices among end users and suggest a predictive model of adoption. The model is based on the UTAUT2 with newer variables identified from the literature. The sample ( n = 253) was collected from four major cities in India, and partial least squares-structural equational model was used to assess the measurement and the structural model. The factors such as ubiquitous, social influence, perceived health risk, and relative advantage had a significant influence on attitude (ATT), which influences behavioral intention (BI) toward IoT-based healthcare devices. Facilitating condition (FC) and price value did not show any significant influence on ATT toward the technology, but FC had a direct influence on BI. The study helps in advancing IS research by adding new variables to the existing knowledge and proposing a model based on UTAUT2. Furthermore, it also brings important practical implications for practitioners.

Open Access February 17, 2023

Early prediction of cardiovascular disease using artificial neural network

Jyotismita Talukdar, Thipendra P. Singh

Article number: 20220107

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Abstract

In recent years, there has been a noticeable rise in the mortality rate, and heart disease is a significant contributor to this trend. According to the California Association for Diabetes Investigation, by 2015, cardiovascular disease would be the primary cause of death in India, where 62 billion people live. Deficiencies in the heart’s ability to pump blood to and from the rest of the body are the leading cause of cardiovascular disease. The healthcare industry is a prime example of a sector poised to greatly benefit from the availability of massive amounts of data and analytical insights. Increasingly, it will be important to extract medical data to predict and treat the high fatality rate caused by heart attacks. Every day, humanity generates terabytes worth of data. Medical errors with dire effects can be avoided only with high-quality services. Hospitals can reduce the price of expensive clinical testing by using decision support systems. Hospitals in the modern-day use hospital information systems to keep track of patient records. The health care sector generates vast amounts of data, but little of it is really put to good use. It will be important to adopt a new strategy to reduce costs and make accurate predictions about heart disease. To determine which machine learning and deep learning approaches are most useful and accurate for predicting and classifying cardiac illnesses, this article reviews the existing literature on the topic and subsequently tries to detect the most probable factors leading to heart disease. This study introduces and models an artificial neural network methodology for identifying potential cardiovascular disease risk factors. In this study, we examine and present the various full and partial correlations among risk attributes. In addition, a number of risk variables are analysed to generate a predicted list of risk features most likely to result in cardiovascular disease.

Open Access March 8, 2023

IoT-Fog-enabled robotics-based robust classification of hazy and normal season agricultural images for weed detection

Isha Kansal, Vikas Khullar, Jyoti Verma, Renu Popli, Rajeev Kumar

Article number: 20220105

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Abstract

The mechanization of farming is currently the most pressing problem facing humanity and a burgeoning academic field. Over the last decade, there has been an explosion of Internet of Things (IoT) application growth in agriculture. Agricultural robotics is bringing about a new era of farming because they are growing more intelligent, recognizing causes of variation on the farm, consuming fewer resources, and optimizing their efficiency to more flexible jobs. The purpose of this article is to construct an IoT-Fog computing equipped robotic system for the categorization of weeds and soy plants during both the hazy season and the normal season. The used dataset in this article included four classes: soil, soybean, grass, and weeds. A two-dimensional Convolutional Neural Network (2D-CNN)-based deep learning (DL) approach was implemented for data image classification with dataset of height and width of 150 × 150 and of three channels. The overall proposed system is considered an IoT-connected robotic device that is capable of applying classification through the Internet-connected server. The reliability of the device is also enhanced as it is enabled with edge-based Fog computing. Hence, the proposed robotic system is capable of applying DL classification through IoT as well as Fog computing architecture. The analysis of the proposed system was conducted in steps including training and testing of CNN for classification, validation of normal images, validation of hazy images, application of dehazing technique, and at the end validation of dehazed images. The training and validation parameters ensure 97% accuracy in classifying weeds and crops in a hazy environment. Finally, it concludes that applying the dehazing technique before identifying soy crops in adverse weather will help achieve a higher classification score.

Open Access April 21, 2023

Application of vibration compensation based on image processing in track displacement monitoring

Ping Yu, Honglin Wang

Article number: 20220090

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Abstract

The track state detection is of great significance to timely understand the operation state of track and find track defects and prevent operation accidents. This article initially analyzes the key technologies of track detection system and then proposes an image detection technology and image processing method for analyzing track detection at home and abroad, thus putting forward the scheme of track detection using image processing. The characteristics of onsite track images are analyzed, and a track state detection system based on track image preprocessing, image position correction, image defect comparison, and track section size measurement is designed in this article. Further in this article, a study of image linear transformation, noise filtering, defect recognition, and edge detection in track image processing is applied. Furthermore, a robust piecewise linear transformation is designed using the combination of image threshold transformation and image gray transformation. It reduces the loss of detailed information in the process of image processing. The center point of track bright band is determined by the image region segmentation method, which effectively reduces the error of image track measurement and improves the measurement accuracy.

Open Access April 28, 2023

Control optimization of taper interference coupling system for large piston compressor in the smart industries

Wenwen Sun, Huifang Xia

Article number: 20220094

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Abstract

To study the control optimization of conical interference connection system for large piston compressor, the reliability optimization and reliability optimization design of conical interference connection were systematically described. By using the proposed method, the maximum operating reliability can be obtained under the condition of constant interference joint size, namely, reliability optimization. Alternatively, the desired working reliability can be designed into the mating connection by optimizing parameters (combining size and interference), namely, reliability optimization design. Design value of 2.12 compression ratio is significantly higher than the unit level. As a result, the mid-stage exhaust temperature of the unit is as high as 124°C, and it is in high temperature operation state. It has been proved that conical interference connection is widely used in hydraulic transmission device because of its advantages of simple structure, reliable operation, and ability to bear certain impact load, reliable transmission torque than general connection, and convenient assembly and disassembly and has been proved to be reliable in practice.

Open Access April 28, 2023

Vibration and control optimization of pressure reducer based on genetic algorithm

Ruiyun HuangFu, Yongyan Zhao

Article number: 20220091

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Abstract

A research challenge of vibration and control optimization of pressurized reducer is solved in this article; a method based on genetic algorithm (GA) is proposed to optimize the vibration and control of reducer. Considering the bending strength of helical gear root and tooth surface contact fatigue strength as constraints, the improved GA is used to solve it, and the optimal parameter combination is obtained. The size of center distance is reduced by 9.59% compared with that before. Based on the optimized results, the vibration becomes weaker with the increase of the load at the output end of the reducer, and its maximum value is only 1/8 of that when the load is 550 N. The experimental results show the optimized surface load distribution of driving gear teeth. The maximum normal load per unit length of the optimized output stage driving gear surface is 521.321 N/mm, which is significantly lower than the 662.455 N/mm before optimization. At the same time, the tooth surface load is evenly distributed. The larger tooth surface load is mainly distributed in the middle of the tooth surface with strong bearing capacity, which effectively solves the problem of unbalanced load before optimization and improves the bearing capacity of gear transmission. It is proved that GA can effectively realize the vibration and control optimization of pressurized reducer.

Open Access May 3, 2023

Real-time image defect detection system of cloth digital printing machine

Hongliang Liu

Article number: 20220099

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Abstract

In order to solve the surface defects such as white silk, spots and wrinkles in the process of digital printing, a surface defect detection system for printed fabrics based on accelerated robust feature algorithm was proposed. Image registration is mainly carried out through accelerated robust feature (SURF); bidirectional unique matching method is adopted to reduce mismatch points, achieve accurate image registration, and extract defect information through differential algorithm. The performance of the improved surfing algorithm is verified by using multiple images. The experimental results show that compared with the traditional template matching method, the detection accuracy of the system detection algorithm is 12% higher, and the average time is 42.81 ms shorter than the traditional template matching method. Experiments show that the improved surfing algorithm has short time and high precision. The system can meet the actual production needs. The new system can detect surface defects on printed fabrics with an accuracy of 98%. Conclusion: The algorithm has higher detection rate and faster detection speed, which can meet the needs of practical industrial applications.

Open Access May 3, 2023

Ultra-low latency communication technology for Augmented Reality application in mobile periphery computing

Bharathiraja Nagu, Thiruneelakandan Arjunan, Manoj L. Bangare, Pradeepa Karuppaiah, Gaganpreet Kaur, Mohammed Wasim Bhatt

Article number: 20220112

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Abstract

Improved Reliability and Low Latency Communication (IRLC) with Augmented Reality (AR) has become an emerging technology in today’s world. To minimize an accessory adaptation for Customer Equipment (CE) in AR, it may be feasible to offload the AR workload onto the onboard devices. Mobile-Edge Computation (MEC) will improve the throughput of a CE. MEC has caused enormous overhead or communication omissions on wireless media, making it difficult to choose the optimal payload proposition. The proposed system explores on-board devices that work together to achieve an AR goal. Code splitting is a Bayesian network used to examine the overall interdependence of efforts. From a longevity and endurance perspective, it is used to reduce the Probability of Supplier Failure (PSF) of an MEC-enabled AR environment. Weighed Particle Swarm Optimization (WPSO) was proposed despite the reality based on the emphasis on balancing the issue. As a result, a heuristic-based WPSO facilitates to improve the performance measures. A hybrid method could significantly increase the assertion of a predicted PSF in various network scenarios compared to the existing communication technologies. A preliminary iterative approach is suitable for AR operations and IRLC scenarios to generalize the attributes.

Open Access May 5, 2023

Improved GA-PSO algorithm for feature extraction of rolling bearing vibration signal

Lixia Hao

Article number: 20220092

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Abstract

To better extract the characteristics of rolling bearing vibration signals, the author proposes a method based on improved genetic algorithm-particle swarm optimization (GA-PSO) algorithm. The common time-domain and frequency-domain feature index construction vectors were extracted based on vibration signals, for signal prediction, by establishing an improved particle swarm algorithm, and by optimizing the signal feature model of the support vector machine (SVM), the signal of the rolling bearing was predicted. The experimental results show that: After the author’s improved particle swarm algorithm optimizes SVM, the signal characteristic accuracy of the bearing is significantly higher, the regression fitting curve is smoother, although the fitting trend is basically the same, the error is significantly higher, this shows that it is feasible to optimize SVM’s rolling bearing signal characteristics based on particle swarm optimization, and proved the author’s improvement of the particle swarm algorithm, it is effective in optimizing SVM parameters. It is proved that the improved GA-PSO algorithm can better extract the characteristics of the vibration signal of the rolling bearing.

Open Access May 10, 2023

COVID bell – A smart doorbell solution for prevention of COVID-19

Abhishek Gudipalli, Vaibhav Kejriwal, Vaishnavi Patel, Riddhi Gupta, Utkarsh Dixit

Article number: 20220115

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Abstract

The article introduces a novel strategy for efficiently mitigating COVID-19 distribution at the local level due to contact with any surfaces. Our project aims to be a critical safety shield for the general people in the fight against the epidemic. An ultrasonic sensor is integrated with the automated doorbell system to ring the doorbell with a hand motion. A temperature sensor Mlx90614 is also included in the system, which records the temperature of the person standing in front of the door. The device also includes a camera module that captures the image of the person standing at the front entrance. The captured image is processed through an ML model which runs at over 30 fps to detect whether or not the person is wearing a mask. The image and the temperature of the person standing outside are sent to the owner through the configured iOS application. If the person outside is wearing a mask, one can open the door through the app itself and permit the entry of the person standing outside thereby integrating the edge device with an app for a better user experience. The system helps in reducing physical contact, and the results obtained are at par with the already existing solutions and provide a few advantages over them.

Open Access May 25, 2023

Mechanical equipment fault diagnosis based on wireless sensor network data fusion technology

Fang Hao, Qiuping Yang, Anjali Sharma, Vipin Balyan

Article number: 20220097

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Abstract

To save network energy consumption and prolong network life cycle in complex mechanical fault diagnosis, a research method of data fusion routing protocol algorithm based on wireless sensor network (WSN) is proposed. The specific content of the method is as follows: First, the low-energy adaptive clustering hierarchy algorithm is analyzed and discussed. On this basis, the prim route fusion algorithm is proposed to realize the effective utilization of energy and prolong the life of the network. Then, the WSN is abstracted as an undirected graph. From the perspective of saving the energy of the whole network, several current algorithms for building fusion trees are compared. The experimental results show that the prim algorithm consumes energy only after 700 rounds of clustering, while the leach clustering algorithm consumes energy only after 500 rounds. This shows that applying the prim algorithm can reduce the energy consumption of the whole network and prolong the life cycle of the network. However, the algorithm is carried out on the premise of uniform distribution of nodes, and there is a certain gap with the specific application of WSN in mechanical fault diagnosis. In the comparison of node energy consumption, it is found that compared with using the shortest path tree, using the central point of graph algorithm can greatly save the energy consumption of the node and has better performance. Practice has proved that this method can effectively remove redundant data information and solve the problem of unreliable data collected by a single sensor node. It is more suitable for the specific application of WSN in mechanical fault diagnosis.

Open Access May 26, 2023

Deep auto-encoder network for mechanical fault diagnosis of high-voltage circuit breaker operating mechanism

Qiuping Yang, Fang Hao

Article number: 20220096

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Abstract

To improve the accuracy of the mechanical fault diagnosis of the operating mechanism and fully exploit the characteristic information in the vibration signal of the high-voltage circuit breaker, a mechanical fault diagnosis method of the operating mechanism of the high-voltage circuit breaker based on the deep self-encoding network is proposed. First, the vibration signal of the switch operating mechanism is extracted, the wavelet packet conversion is performed, and the vibration signal of each frequency band is divided into equal times. The energy of the time–frequency subplane of the vibration signal is then calculated, and the time–frequency energy distribution is used as a switch. Finally, a breaker failure diagnostic model based on the deep self-coding network is established. Pretraining and tuning and a 126 kV high-voltage switch are used to simulate different types of faults and validate the method. Experimental results show that this method can acquire sample failure data and perform failure diagnosis, and the diagnosis accuracy rate reaches 97.5%. The deep self-coding network can fully pierce deep information on the switch vibration signal.

Open Access May 29, 2023

Control strategy for plug-in electric vehicles with a combination of battery and supercapacitors

Mallu Rama Prasad Reddy, Subramanya Sarma Saraswathula, Vangala Naga Siva Rama Murthy, Challagulla Kesava Tripureswari Sita Raghava Kowstubha

Article number: 20220111

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Abstract

Research proposes an optimal power distribution approach for application of electric vehicle (EV) with use of hybrid energy storage system (HESS). HESS protection structure includes dual isolated-based soft-switching symmetrical coupling with half-bridge bidirectional converters to the system of battery and supercapacitors (SCs). The bidirectional converter properly controls the charging process of the battery and SC as well. Besides, spiral wound SCs of mesoporous electrode material have been used in EVs. In the drive cycle of EVs, the operation of SC relates to the functionality of the allocated scheme under “peak load transfer” at 2 i sc ∼ 3 i bat current profile carried out. New energy allocation strategies under SOC control enable SC charging and discharging at peak currents of around 4 i bat . The comparison of the mode of the battery system showed that the performance acceleration built under EVs has been improvised at a certain rate of 50% with a loss of energy minimised to 69%. As a result, the technique adapts different load curves, thus enhancing the utilisation of energy with reduced aging of the battery. The simulation results show that the proposed scheme meets the power demand of a typical driving cycle, for testing vehicle performance, and various energy management system have been assessed based on hydrogen consumption, overall efficiency, state of charge of SCs and batteries, stress on hybrid sources, and DC bus stability. The proposed strategy reduces hydrogen consumption by 8.7% compared to other strategies.

Open Access May 29, 2023

Reconfigurable intelligent surface with 6G for industrial revolution: Potential applications and research challenges

Ashish K. Singh, Ajay K. Maurya, Ravi Prakash, Prabhat Thakur, Brij Bihari Tiwari

Article number: 20220114

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Abstract

With proper tuning in the phase shift of reconfigurable intelligent surfaces (RISs) or intelligent reflecting surfaces (IRSs), which consist of huge number of passive reflecting elements, are the most promising and transforming technology to reconfigure the wireless propagation ecosystems to improve the “spectral-and energy-efficiency” for the future generation wireless communication system. This article presents a systematic review of RIS/IRS technology and conceptualizes the prospective requirement, operations, and application. Further, we have presented its capability for execution in a forthcoming smart industrial ecosystem to assist the development of Industry 5.0 with a series of emerging applications. Finally, we discuss the potential, open research challenges, and prospects of RIS technology in the emerging intelligent manufacturing industry to encourage future research in this area.

Roboethics

Open Access May 5, 2023

Discrimination against robots: Discussing the ethics of social interactions and who is harmed

Jessica K. Barfield

Article number: 20220113

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Abstract

This article discusses the topic of ethics and policy for human interaction with robots. The term “robot ethics” (or roboethics) is generally concerned with ethical problems that may occur when humans and robots interact in social situations or when robots make decisions which could impact human well-being. For example, whether robots pose a threat to humans in warfare, the use of robots as caregivers, or the use of robots which make decisions which could impact historically disadvantaged populations. In each case, the focus of the discussion is predominantly on how to design robots that act ethically toward humans (some refer to this issue as “machine ethics”). Alternatively, robot ethics could refer to the ethics associated with human behavior toward robots especially as robots become active members of society. It is this latter and relatively unexplored view of robot ethics that this article focuses on, and specifically whether robots will be the subject of discriminatory and biased responses from humans based on the robot’s perceived race, gender, or ethnicity. If so, the paper considers what issues are implicated, and how society might respond? From past research, preliminary evidence suggests that acts of discrimination which may be directed against people may also be expressed toward robots experienced in social contexts; therefore, discrimination against robots as a function of their physical design and behavior is an important and timely topic of discussion for robot ethics, human–robot interaction, and the design of social robots.

Volume 4 (2013)

Volume 3 (2012)

Volume 2 (2011)

Volume 1 (2010)

CiteScore	3.8
Index Copernicus Value	133.57
SCImago Journal Rank	0.517
Source Normalized Impact per Paper	0.936

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MANUSCRIPTS
Paladyn, Journal of Behavioral Robotics encourages the submission of substantial full-length bodies of work. There are no specific length restrictions for the overall manuscript or individual sections; however, we urge the authors to present and discuss their findings in a concise and accessible manner.

Manuscripts should be submitted to the journal via online submission system Editorial Manager available for this journal at http://www.editorialmanager.com/paladyn/. In case of problems, please contact the Editorial Office of this journal via email paladyn@degruyter.com.

Manuscripts can be written in TeX, LaTeX (strongly recommended). Please note that we do not accept papers in Plain TEX format. Text files can be also submitted as standard DOCUMENT (.DOC) which is acceptable if the submission in LATEX is not possible. For an initial submission, the authors are strongly advised to upload their entire manuscript, including tables and figures, as a single PDF file. Authors are strongly advised to submit the final version of the paper using the journal’s LATEX template.
For detailed information, please see Instructions for Authors.

EDITORIAL POLICY
Unpublished material: Submission of a manuscript implies that the work described is not copyrighted, published or submitted elsewhere, except in abstract form. The corresponding author should ensure that all authors approve the manuscript before its submission.
Ethical conduct of research: The authors must describe and confirm safeguards to meet ethical standards when applicable. See Editorial Policy for details.
Conflict of interest: When authors submit a manuscript, they are responsible for recognizing and disclosing financial and/or other conflicts of interest that might bias their work and/or could inappropriately influence his/her judgment. If no specified acknowledgement is given, the Editors assume that no conflict of interest exists. Authors are encouraged to fill in the ICMJE Conflicts of Interest Form (available here) and send it in the electronic format to the Managing Editor.
Copyright: All authors retain copyright, unless – due to their local circumstances – their work is not copyrighted.
The copyrights are governed by the Creative-Commons Attribution Only license (CC-BY) which is compliant with Plan-S. The corresponding author grants the journal the license to use of the article, by signing the License to Publish. Scanned copy of license should be sent to the journal, as soon as possible.
Authorship: Authorship should be limited to those who have made a significant contribution to the conception, design, execution, or interpretation of the reported study. All those who have made significant contributions should be listed as co-authors. Where there are others who have participated in certain substantive aspects of the research project, they should be named in an Acknowledgement section. The corresponding author should ensure that all appropriate co-authors (according to the above definition) and no inappropriate co-authors are included in the author list of the manuscript, and that all co-authors have seen and approved the final version of the paper and have agreed to its submission for publication.
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Peer Review process: Our standard policy requires each paper to be reviewed by at least two Referees and the peer-review process is single-blind. The Editors reserve the right to decline the submitted manuscript without review, if the studies reported are not sufficiently novel or important to merit publication in the journal. Manuscripts deemed unsuitable (insufficient originality or of limited interest to the target audience) are returned to the author(s) without review. The Editor seeks advice from experts in the appropriate field. Research articles and communications are refereed by a minimum of two reviewers, review papers by at least three. Authors are requested to suggest persons competent to review their manuscript. However, please note that this will be treated only as a suggestion, and the final selection of reviewers is exclusively the Editor's decision. The final decision of acceptance is made by Managing Editor or, in case of conflict, by the Editor-in-Chief.
Scientific Misconduct: This journal publishes only original manuscripts that are not also published or going to be published elsewhere. Multiple submissions/publications, or redundant publications (re-packaging in different words of data already published by the same authors) will be rejected. If they are detected only after publication, the journal reserves the right to publish a Retraction Note. In each particular case Editors will follow COPE’s Core Practices and implement the advices.

SUBMISSION OF MANUSCRIPTS
Manuscripts have to be written in LATEX, AMS-TEX, AMS-LATEX. We do not accept papers in Plain TEX format. If additionally a PDF file is supplied, the peer review process will speed up. Authors are encouraged to submit the final version of the paper using the De Gruyter Open LATEX template. For detailed information, please see Instruction for Authors.

EDITORIAL POLICY
The journal uses a single-blind peer review system.
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Peer Review process: Our standard policy requires each paper to be reviewed by at least two Referees and the peer-review process is single-blind. The Editors reserve the right to decline the submitted manuscript without review, if the studies reported are not sufficiently novel or important to merit publication in the journal. Manuscripts deemed unsuitable (insufficient originality or of limited interest to the target audience) are returned to the author(s) without review. The Editor seeks advice from experts in the appropriate field. Research articles and communications are refereed by a minimum of two reviewers, review papers by at least three. Authors are requested to suggest persons competent to review their manuscript. However, please note that this will be treated only as a suggestion, and the final selection of reviewers is exclusively the Editor's decision. The final decision of acceptance is made by the Managing Editor or, in case of conflict, by the Editor-in-Chief.
Scientific Misconduct: This journal publishes only original manuscripts that are not also published or going to be published elsewhere. Multiple submissions/publications, or redundant publications (re-packaging in different words of data already published by the same authors) will be rejected. If they are detected only after publication, the journal reserves the right to publish a Retraction Note. In each particular case, Editors will follow COPE's Code of Conduct and implement its advice.

Editorial

Editor-in-Chief
Adrian D. Cheok, iUniversity Tokio, Japan
Gregor Schöner, Ruhr-Universität Bochum, Germany

Associate Editors
Antonio Andriella, PAL Robotics, Spain
Kim Baraka, Vrije Universiteit Amsterdam, The Netherlands
Erik Billing, University of Skövde, Sweden
Patrick Holthaus, University of Hertfordshire, UK
Sabine T. Köszegi, Technische Universität Wien, Austria
Alessandra Rossi, University of Hertfordshire, UK
Ashutosh Sharma, University of Petroleum and Energy Studies, Dehradun, India

Editorial Advisory Board
Gerardo Beni, University of California, USA
Angelo Cangelosi, University of Manchester, UK
Marco Dorigo, Université Libre de Bruxelles, Belgium
Chrystopher Nehaniv, University of Waterloo, Canada / University of Hertfordshire, UK
Radu-Emil Precup, Politehnica University of Timisoara, Romania
Fiorella Operto, The School of Robotics, Italy
Nilanjan Sarkar, Vanderbilt University, USA
Sergiu Dan Stan, Technical University of Cluj-Napoca, Cluj-Napoca, Romania

Editorial Board
Dario Cazzato, University of Luxembourg, Luxembourg
Ignazio Infantino, Institute of High Performance Computing and Networking (ICAR), National Research Council (CNR), Italy
Basilio Lenzo, Sheffield Hallam University, UK
Qiang Li, CITEC, Bielefeld University, Germany
Kanstantsin Miatliuk, Bialystok University of Technology, Poland
Marcin Miłkowski, Polish Academy of Science, Poland
Slawomir Nasuto, University of Reading, UK
Rui Paulo Rocha, Universidade de Coimbra, Portugal
Nazmul Haque Siddique, University of Ulster, UK
Tadeusz Stepinski, AGH – University of Science and Technology, Kraków, Poland
Ian van der Linde, Anglia Ruskin University, Cambridge, UK
Neil Vaughan, University of Exeter, UK
Mattias Wahde, Chalmers University of Technology, Sweden
Cezary Zieliński, Warsaw University of Technology, Poland

Honorary Editor
Lech Polkowski, University of Warmia and Mazury in Olsztyn, Poland

Managing Editor
Katarzyna Gajewska, De Gruyter
Katarzyna.Gajewska@degruyter.com

Publisher
DE GRUYTER Poland
Bogumila Zuga 32A Str.
01-811 Warsaw, Poland
T: +48 22 701 50 15

Editorial Contact
paladyn@degruyter.com

(Deutsch)

Type: Journal
Language: English
Publisher: De Gruyter Open Access
First published: March 1, 2010
Publication Frequency: 1 Issue per Year
Audience: engineers, computer scientists, physicists, neuroscientists, psychologists, sociologists