Advanced Robotics (Adv Robot )

Publisher: Robotics Society of Japan, Brill Academic Publishers


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.

  • Impact factor
  • 5-year impact
  • Cited half-life
  • Immediacy index
  • Eigenfactor
  • Article influence
  • Website
    Advanced Robotics website
  • Other titles
    Advanced robotics, Advanced robotics online
  • ISSN
  • OCLC
  • Material type
  • Document type
    Journal / Magazine / Newspaper

Publisher details

Brill Academic Publishers

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Pre-print can only be deposited after acceptance for peer-review
    • Author may post on authors own website only
    • Publisher version may be posted on authors own website
    • Institution may post on institutional website/ repository only
    • Publisher's version/PDF cannot be used in institutional repository
    • Must link to publisher version
    • Published source must be acknowledged
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a method for the fast calculation of a robot’s egomotion using visual features. The method is part of a complete system for automatic map building and Simultaneous Location and Mapping (SLAM). The method uses optical flow to determine whether the robot has undergone a movement. If so, some visual features that do not satisfy several criteria are deleted, and then egomotion is calculated. Thus, the proposed method improves the efficiency of the whole process because not all the data is processed. We use a state-of-the-art algorithm (TORO) to rectify the map and solve the SLAM problem. Additionally, a study of different visual detectors and descriptors has been conducted to identify which of them are more suitable for the SLAM problem. Finally, a navigation method is described using the map obtained from the SLAM solution.
    Advanced Robotics 09/2014; 28(18):1231-1242.
  • [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.
  • Advanced Robotics 06/2014; 28(13).
  • [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.
  • Advanced Robotics 01/2014; 28(6):403-414.
  • [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.
  • [Show abstract] [Hide abstract]
    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;
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper the problem of patrolling an environment with a dynamic team of robots is targeted. Lately, the interest of the research community has been focused in the development of patrol strategies; however there is a deficit of studies comparing such strategies, namely in terms of their performance and team scalability in different environments. For this reason, an evaluation of five representative patrol approaches is presented in this article. Aiming to analyze the performance, ability to scale and the behavior resulting from interactions between teammates, extensive realistic simulation using ROS together with Stage was conducted. The metric used to compare the performance is the average idleness of the topological environment (i.e. graph), that represents the area to patrol. The results presented help to identify which strategies enable enhanced team scalability and which are the most suitable approaches given any environment, supporting future research directions in the field.
    Advanced Robotics 02/2013; 27(5):325-336.
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, we propose new denoising techniques for a deteriorated range image taken by a laser scanner. Laser scanner acquires a range value from the scanner to the target by measuring the round-trip time of the emitted laser pulse. At the same time, they can obtain the strength of the reflected light as a side product of the range value. Focusing on the laser intensity, we propose two denoising techniques for a deteriorated range image utilizing the intensity image: smoothing by extended bilateral filter, and completion by belief propagation. The extended bilateral filter makes use of laser intensity in addition to the spatial and range information in order that we can smooth a range image corrupted by noises while the geometric features such as jump and roof edges are preserved. The range image completion technique with belief propagation restores a deteriorated range image using the adjacent range values and the corresponding intensity values simultaneously. We conduct simulations and experiments using synthesized images and actual range images taken by a laser scanner and verify that the proposed techniques suppress noise while preserving jump and roof edges and repair deteriorated range images.
    Advanced Robotics 01/2013; 27(12):947-958.
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a novel method for the online estimation of variance parameters regulating the dynamics of a nonlinear dynamic system. The approach exploits and extends classical iterated Kalman filtering equations by propagating an approximation of the marginal posterior of the unknown variances over time. In addition to the theoretical foundations, this manuscript offers also a variety of numerical results. In particular, experiments with data collected both in simulation and with a real robot platform show how the proposed approach efficiently solves a robot localization problem.
    Advanced Robotics 09/2012; 26(18):2169-2188.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a sliding mode filter for removing noise. It effectively removes impulsive noise and highfrequency noise, producing a smaller phase lag than linear filters. In addition, it is less prone to overshoot than previous sliding mode filters and it does not produce chattering. It is computationally inexpensive and thus suitable for real-time applications. The proposed sliding mode filter employs a quadratic surface as its sliding surface, which is designed so that the output converges to the input in finite time when the input value is constant. Its algorithm is derived by using the backward Euler discretization, which can be used to prevent chattering. The effectiveness of the filter was shown by experiments using an ultrasonic sensor and an optical encoder.
    Advanced Robotics 07/2012; 26(8-9):877-896.

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