Advanced Robotics (Adv Robot)

Publisher: Robotics Society of Japan, Taylor & Francis

Journal description

The international journal of the Robotics Society of Japan. Published jointly with the Robotics Society of Japan. Advanced Robotics is the international bimonthly journal of the Robotics Society of Japan. The journal meets the demand for an international interdisciplinary journal which integrates publication of all aspects of research on robotics science and engineering with special emphasis being placed on work done in Japan. Although founded as the International Journal of the Robotics Society of Japan, researchers in every country are welcomed to submit papers for publication in the journal. Advanced Robotics publishes original research papers, short communications, reviews and reports. Issues contain papers on the analysis, design, implementation and use of robots in various areas such as manipulators, locomotion, sensors, actuators, materials, control, intelligence, language, software, man-machine systems and system architecture. The journal also covers aspects of social and managerial analysis and policy regarding robots.

Current impact factor: 0.57

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 0.572
2013 Impact Factor 0.562
2012 Impact Factor 0.51
2011 Impact Factor 0.571
2010 Impact Factor 0.653
2009 Impact Factor 0.629
2008 Impact Factor 0.737
2007 Impact Factor 0.504
2006 Impact Factor 0.318
2005 Impact Factor 0.348
2004 Impact Factor 0.254
2003 Impact Factor 0.375
2002 Impact Factor 0.182
2001 Impact Factor 0.111
2000 Impact Factor 0.09
1999 Impact Factor 0.225
1998 Impact Factor 0.138
1997 Impact Factor 0.133
1996 Impact Factor 0.062

Impact factor over time

Impact factor

Additional details

5-year impact 0.65
Cited half-life 6.70
Immediacy index 0.05
Eigenfactor 0.00
Article influence 0.21
Website Advanced Robotics website
Other titles Advanced robotics, Advanced robotics online
ISSN 1568-5535
OCLC 67249706
Material type Periodical
Document type Journal / Magazine / Newspaper

Publisher details

Taylor & Francis

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Some individual journals may have policies prohibiting pre-print archiving
    • On author's personal website or departmental website immediately
    • On institutional repository or subject-based repository after either 12 months embargo
    • Publisher's version/PDF cannot be used
    • On a non-profit server
    • Published source must be acknowledged
    • Must link to publisher version
    • Set statements to accompany deposits (see policy)
    • The publisher will deposit in on behalf of authors to a designated institutional repository including PubMed Central, where a deposit agreement exists with the repository
    • STM: Science, Technology and Medicine
    • Publisher last contacted on 25/03/2014
    • This policy is an exception to the default policies of 'Taylor & Francis'
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, a simple yet proficient approach for the recognition of Human Action and Activity is presented. This method is based on the integration of translation and rotation of the human body. The proposed framework under goes three major steps: i) the shape of human action/activity is represented through the computation of average energy images using edge spatial distribution of gradients along with the directional variation of the pixel values, ii) The orientation based rotational information of the human action is computed through R–transform, iii) A descriptor is developed by fusion of translational features with rotational features. The fusion of features possesses the advantages exhibited by both local and global features of the silhouette and thus provides the discriminating feature representation for human activity recognition. The performance of descriptor is evaluated through a hybrid approach of support vector machine (SVM) and nearest neighbour (NN) classifiers on standard dataset. The proposed method has shown superior results in terms of recognition accuracy in comparison with other state-of-the-art methods.
    Advanced Robotics 06/2015; DOI:10.1080/01691864.2015.1061701
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    ABSTRACT: The energy or efficiency produced by solar photovoltaic modules is related with the Sun’s available irradiance and spectral content, as well as other factors like environmental, climatic, component performance and inherent system. These dust, dirt and bird droppings are the major reasons for the solar photovoltaic system under performance. This paper discusses a comprehensive overview of dust problem and the recent developments made on automated cleaning system for solar photovoltaic modules which give brief overview on techniques like electrical, mechanical, chemical and electrostatic. The main objective of the study is to review the literature on solar photovoltaic module automated cleaning techniques for identifying research gaps in the automated cleaning systems.
    Advanced Robotics 04/2015; 29(8):515- 524. DOI:10.1080/01691864.2014.996602
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    ABSTRACT: This paper deals with an efficient implementation of an H∞ multi-variable controller on the three degrees of freedom (DOF) parallel robot namely the ‘Delta robot’. The H∞ controller is designed by the mixed sensitivity approach in which the sensitivity function matrix S and the complementary sensitivity function matrix T are taken into account. For this purpose, a nonlinear analytical dynamic state model is developed and a tangent linearization procedure is used to obtain a multi-variable linear model around a functional point. Real-time experiments were performed to compare the centralized H∞ controller with a classical decentralized Proportional Integral Derivative (PID) controller. Experimental tracking results show that the performances of the PID compared to those of the H∞ decrease when the movement dynamic is increased. At high dynamic (12 Ge), it is shown that the maximum tracking error and the error around the stop positions of the H∞ are, respectively, 80 and 60% of the PID. The experiments of the load variation have proven that the H∞ is more robust than the PID. The steady-state root mean square error of the H∞ is less than 60% of the one obtained using the PID controller
    Advanced Robotics 04/2015; DOI:10.1080/01691864.2015.1046924
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    ABSTRACT: This study proposed an online reference governor for a mobile robot to reduce the occurrence of control input saturation. For following the trajectory by a mobile robot, it is one of the practical subjects to provide appropriate control reference even if any disturbances occur. We proposed a methodology to regulate the control reference iteratively based on time-scaling approach. The time-scaling approach is a method to realize to regulate time development characteristic on the given trajectory. It is difficult to model the effect of the interaction with the road surface and the trajectory tracking error is appeared as the amount of accumulated such factors. Therefore, it is a practical approach to reduce the occurrence of control input saturation based on the evaluation of the trajectory tracking error. Proposed reference governor realizes online time scaling based on the trajectory tracking error index and a smooth transition dynamics. By introducing the proposed method, the occurrence of control input saturation can be reduced in case of that the disturbances occur. For verification of our proposed method, computer simulations utilizing a stable velocity controller were conducted and the results were discussed.
    Advanced Robotics 01/2015; DOI:10.1080/01691864.2014.1001789
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    ABSTRACT: pherical robots provide an exploration platform that enables the access to inaccessible or dangerous places to people. These robots are also capable of hiding their components inside themselves, protecting in that way their integrity. Even though these robots are capable of moving over irregular surfaces, they face difficulties when moving over surfaces with hollows, stairs, or slopes. We propose a sea urchin-like robot, a spherical robot equipped with retractable devices within its body. This robot overcomes some disadvantages of spherical robots, concerning namely locomotion over irregular surfaces. The robot is capable of moving over irregular surfaces with hollows up to of its diameter, a significant gain to the known constraint of objects and hollows of 1/10 of their diameter that traditional spherical robots are able to deal with. The main contribution of this work is a model of a flexible vehicle able to traverse irregular surfaces required in remote sensing missions.
    Advanced Robotics 11/2014; 28(22):1475-1485. DOI:10.1080/01691864.2014.968615#.VG4xYEvv1vA
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, a hierarchical multi-classification approach using support vector machines (SVM) has been proposed for road intersection detection and classification. Our method has two main steps. The first involves the road detection. For this purpose, an edge-based approach has been developed using the bird’s eye view image which is mapped from the perspective view of the road scene. Then, the concept of vertical spoke has been introduced for road boundary form extraction. The second step deals with the problem of road intersection detection and classification. It consists on building a hierarchical SVM classifier of the extracted road forms using the unbalanced decision tree architecture. Many measures are incorporated for good evaluation of the proposed solution. The obtained results are compared to those of Choi et al. (2007).
    Advanced Robotics 07/2014; DOI:10.1080/01691864.2014.902327
  • [Show abstract] [Hide abstract]
    ABSTRACT: In position control of mechatronic devices, velocity feedback is important for injecting additional damping to avoid low-frequency fluctuation around desired trajectories. In practice, velocity signal is often obtained by finite difference of position signal from an optical encoder. However, such a numerical differentiation produces high-frequency noise by magnifying quantization error contained in the position signal. As a result, the controller may produce high-frequency vibration. This paper presents a new noise-reduction discrete-time filter based on sliding mode and adaptive windowing. The presented filter is an improved version of a sliding mode filter by Jin et al. (2012), with including adaptive windowing of which the window size is determined in a similar way to that of a discrete-time adaptive windowing differentiator by Janabi-Sharifi et al. (2000). The presented filter is then applied to a position control of a mechatronic device for improving velocity feedback. Experimental results show that the presented filter provides better velocity feedback than its previous version, Janabi-Sharifi et al.’s differentiator, and combinations of these two filters.
    Advanced Robotics 07/2014; 28(14):943-953. DOI:10.1080/01691864.2014.899161
  • Advanced Robotics 06/2014; 28(13).
  • [Show abstract] [Hide abstract]
    ABSTRACT: We propose control of a snake robot that can switch lifting parts dynamically according to kinematics. Snakes lift parts of their body and dynamically switch lifting parts during locomotion: e.g. sinus-lifting and sidewinding motions. These characteristic types of snake locomotion are used for rapid and efficient movement across a sandy surface. However, optimal motion of a robot would not necessarily be the same as that of a real snake as the features of a robot’s body are different from those of a real snake. We derived a mathematical model and designed a controller for the three-dimensional motion of a snake robot on a two-dimensional plane. Our aim was to accomplish effective locomotion by selecting parts of the body to be lifted and parts to remain in contact with the ground. We derived the kinematic model with switching constraints by introducing a discrete mode number. Next, we proposed a control strategy for trajectory tracking with switching constraints to decrease cost function, and to satisfy the conditions of static stability. In this paper, we introduced a cost function related to avoidance of the singularity and the moving obstacle. Simulations and experiments demonstrated the effectiveness of the proposed controller and switching constraints.
    Advanced Robotics 01/2014; 28(6):415-429. DOI:10.1080/01691864.2013.867285
  • [Show abstract] [Hide abstract]
    ABSTRACT: The real-world applicability of modern computer vision and recognition applications is limited by its real-time performance. Hardware-based systems can provide fast solutions for real-time limited problems; however, hardware-friendly solutions usually lack the flexibility to handle highly complex tasks. On the other hand, software-based solutions are used to tackle complex tasks and allow for greater flexibility but lack the speeds which hardware systems can provide. Inspired by the function of the human memory, we propose a hardware-accelerated multi-prototype and nearest neighbor (NN) search-based learning and classification system, which overcomes these flexibility limitations. A major deficiency for NN-based implementations is the computational demand for the searching and clustering processes. An FPGA-implemented coprocessor architecture for the Euclidean distance search was designed to resolve this deficiency. We benchmarked the system on the complex application of human detection. The experimental results revealed that the system outperformed other implementations by significantly reducing training times and attained a per sample detection speed of 2.24μs.
    Advanced Robotics 01/2014; 28(5):255-265. DOI:10.1080/01691864.2013.870494
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    ABSTRACT: Nowadays, a particular kind of UAVs (Unmanned Aerial Vehicle) known as quadcopters or quadrotors have become very popular. This is mainly due to their reduced size and high maneuverability which allow them to operate in indoor environments. The requirement for orientation estimation in these vehicles is twofold: for low level stability control, and for high level navigation and motion planning. Orientation estimation is usually carried out fusing measurements of different sensors including inertial sensor, magnetic compass, sonar, GPS, camera, etc. As is known, GPS signal is not available in indoor environments and the Earth's magnetic field is highly disturbed by ferromagnetic structures. In the present work we describe a new approach for quadrotor orientation estimation fusing inertial measurements with a downward looking camera. Inertial sensor are used for orientation estimation based on the gravity vector, and the camera provides information related to the heading direction. The camera heading or yaw angle estimation is based on spectral features extracted from the floor plane. Experimental results show the performance of the presented approach applied to a hovering UAV.
    Advanced Robotics 11/2013;