Special Issue "Feature Papers"

A special issue of Robotics (ISSN 2218-6581).

Deadline for manuscript submissions: closed (31 August 2018).

Special Issue Editor

Prof. Dr. Huosheng Hu
Website
Guest Editor
School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK
Interests: robotics; embedded systems; mechatronics; advanced manufacturing; multimodal human-machine interfaces; wearable sensors and systems; sensor integration and data fusion algorithms; biomedical signal processing; e-health; medical and surgical robotics; AI applications; intelligent control and learning algorithms; cooperative robots in search and rescue; networked sensors, systems, and robots
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Special Issue Information

Dear Colleagues,

We plan to publish a Special Issue on "Feature Papers" in order to give a broad overview of the areas covered by the journal. We are looking for high quality papers that contain either cutting-edge research results or comprehensive reviews. The accepted papers will be published free of charge in open access. Authors will be the Editorial Board Members and the researchers invited by the Editorial Office on behalf of Editor-in-Chief. Your support to this special issue is highly appreciated.

Prof. Dr. Huosheng Hu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Robotics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Research

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Open AccessArticle
Representation of Multiple Acoustic Sources in a Virtual Image of the Field of Audition from Binaural Synthetic Aperture Processing as the Head is Turned
Robotics 2019, 8(1), 1; https://doi.org/10.3390/robotics8010001 - 23 Dec 2018
Cited by 1
Abstract
The representation of multiple acoustic sources in a virtual image of the field of audition based on binaural synthetic-aperture computation (SAC) is described through use of simulated inter-aural time delay (ITD) data. Directions to the acoustic sources may be extracted from the image. [...] Read more.
The representation of multiple acoustic sources in a virtual image of the field of audition based on binaural synthetic-aperture computation (SAC) is described through use of simulated inter-aural time delay (ITD) data. Directions to the acoustic sources may be extracted from the image. ITDs for multiple acoustic sources at an effective instant in time are implied for example by multiple peaks in the coefficients of a short-time base (≈2.25 ms for an antennae separation of 0.15 m) cross correlation function (CCF) of acoustic signals received at the antennae. The CCF coefficients for such peaks at the time delays measured for a given orientation of the head are then distended over lambda circles in a short-time base instantaneous acoustic image of the field of audition. Numerous successive short-time base images of the field of audition generated as the head is turned are integrated into a mid-time base (up to say 0.5 s) acoustic image of the field of audition. This integration as the head turns constitutes a SAC. The intersections of many lambda circles at points in the SAC acoustic image generate maxima in the integrated CCF coefficient values recorded in the image. The positions of the maxima represent the directions to acoustic sources. The locations of acoustic sources so derived provide input for a process managing the long-time base (>10s of seconds) acoustic image of the field of audition representing the robot’s persistent acoustic environmental world view. The virtual images could optionally be displayed on monitors external to the robot to assist system debugging and inspire ongoing development. Full article
(This article belongs to the Special Issue Feature Papers)
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Open AccessArticle
Model-Free Gradient-Based Adaptive Learning Controller for an Unmanned Flexible Wing Aircraft
Robotics 2018, 7(4), 66; https://doi.org/10.3390/robotics7040066 - 23 Oct 2018
Cited by 9
Abstract
Classical gradient-based approximate dynamic programming approaches provide reliable and fast solution platforms for various optimal control problems. However, their dependence on accurate modeling approaches poses a major concern, where the efficiency of the proposed solutions are severely degraded in the case of uncertain [...] Read more.
Classical gradient-based approximate dynamic programming approaches provide reliable and fast solution platforms for various optimal control problems. However, their dependence on accurate modeling approaches poses a major concern, where the efficiency of the proposed solutions are severely degraded in the case of uncertain dynamical environments. Herein, a novel online adaptive learning framework is introduced to solve action-dependent dual heuristic dynamic programming problems. The approach does not depend on the dynamical models of the considered systems. Instead, it employs optimization principles to produce model-free control strategies. A policy iteration process is employed to solve the underlying Hamilton–Jacobi–Bellman equation using means of adaptive critics, where a layer of separate actor-critic neural networks is employed along with gradient descent adaptation rules. A Riccati development is introduced and shown to be equivalent to solving the underlying Hamilton–Jacobi–Bellman equation. The proposed approach is applied on the challenging weight shift control problem of a flexible wing aircraft. The continuous nonlinear deformation in the aircraft’s flexible wing leads to various aerodynamic variations at different trim speeds, which makes its auto-pilot control a complicated task. Series of numerical simulations were carried out to demonstrate the effectiveness of the suggested strategy. Full article
(This article belongs to the Special Issue Feature Papers)
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Open AccessArticle
The Development of Highly Flexible Stretch Sensors for a Robotic Hand
Robotics 2018, 7(3), 54; https://doi.org/10.3390/robotics7030054 - 11 Sep 2018
Cited by 12
Abstract
Demand for highly compliant mechanical sensors for use in the fields of robotics and wearable electronics has been constantly rising in recent times. Carbon based materials, and especially, carbon nanotubes, have been widely studied as a candidate piezoresistive sensing medium in these devices [...] Read more.
Demand for highly compliant mechanical sensors for use in the fields of robotics and wearable electronics has been constantly rising in recent times. Carbon based materials, and especially, carbon nanotubes, have been widely studied as a candidate piezoresistive sensing medium in these devices due to their favorable structural morphology. In this paper three different carbon based materials, namely carbon black, graphene nano-platelets, and multi-walled carbon nanotubes, were utilized as large stretch sensors capable of measuring stretches over 250%. These stretch sensors can be used in robotic hands/arms to determine the angular position of joints. Analysis was also carried out to understand the effect of the morphologies of the carbon particles on the electromechanical response of the sensors. Sensors with gauge factors ranging from one to 1.75 for strain up to 200% were obtained. Among these sensors, the stretch sensors with carbon black/silicone composite were found to have the highest gauge factor while demonstrating acceptable hysteresis in most robotic hand applications. The highly flexible stretch sensors demonstrated in this work show high levels of compliance and conformance making them ideal candidates as sensors for soft robotics. Full article
(This article belongs to the Special Issue Feature Papers)
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Open AccessArticle
Kinematics of the 3(RPSP)-S Fully Spherical Parallel Manipulator by Means of Screw Theory
Robotics 2018, 7(2), 29; https://doi.org/10.3390/robotics7020029 - 15 Jun 2018
Abstract
In this work, the kinematics of a spherical parallel manipulator composed of three peripheral limbs equipped with linear actuators and a passive center shaft is approached by means of the theory of screws. The displacement analysis is carried out solving closure equations, which [...] Read more.
In this work, the kinematics of a spherical parallel manipulator composed of three peripheral limbs equipped with linear actuators and a passive center shaft is approached by means of the theory of screws. The displacement analysis is carried out solving closure equations, which are obtained upon simple linear combinations of the components of two unit vectors describing the orientation of the moving platform. After, the input-output equations of velocity and acceleration of the spherical parallel manipulator are systematically obtained by resorting to reciprocal-screw theory. This strategy avoids the computation of the passive joint velocity and acceleration rates of the robot manipulator. Numerical examples illustrate the efficiency of the proposed method. Full article
(This article belongs to the Special Issue Feature Papers)
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Review

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Open AccessReview
Multi-Modal Sensing and Robotic Manipulation of Non-Rigid Objects: A Survey
Robotics 2018, 7(4), 74; https://doi.org/10.3390/robotics7040074 - 20 Nov 2018
Cited by 6
Abstract
This paper aims to provide a comprehensive survey of recent advancements in modelling and autonomous manipulation of non-rigid objects. It first summarizes the recent advances in sensing and modelling of such objects with a focus on describing the methods and technologies used to [...] Read more.
This paper aims to provide a comprehensive survey of recent advancements in modelling and autonomous manipulation of non-rigid objects. It first summarizes the recent advances in sensing and modelling of such objects with a focus on describing the methods and technologies used to measure their shape and estimate their material and physical properties. Formal representations considered to predict the deformation resulting from manipulation of non-rigid objects are then investigated. The third part provides a survey of planning and control strategies exploited to operate dexterous robotic systems while performing various tasks on objects made of different non-rigid materials. Full article
(This article belongs to the Special Issue Feature Papers)
Open AccessReview
Formation Control for a Fleet of Autonomous Ground Vehicles: A Survey
Robotics 2018, 7(4), 67; https://doi.org/10.3390/robotics7040067 - 01 Nov 2018
Cited by 12
Abstract
Autonomous/unmanned driving is the major state-of-the-art step that has a potential to fundamentally transform the mobility of individuals and goods. At present, most of the developments target standalone autonomous vehicles, which can sense the surroundings and control the vehicle based on this perception, [...] Read more.
Autonomous/unmanned driving is the major state-of-the-art step that has a potential to fundamentally transform the mobility of individuals and goods. At present, most of the developments target standalone autonomous vehicles, which can sense the surroundings and control the vehicle based on this perception, with limited or no driver intervention. This paper focuses on the next step in autonomous vehicle research, which is the collaboration between autonomous vehicles, mainly vehicle formation control or vehicle platooning. To gain a deeper understanding in this area, a large number of the existing published papers have been reviewed systemically. In other words, many distributed and decentralized approaches of vehicle formation control are studied and their implementations are discussed. Finally, both technical and implementation challenges for formation control are summarized. Full article
(This article belongs to the Special Issue Feature Papers)
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Open AccessReview
Robot Learning from Demonstration in Robotic Assembly: A Survey
Robotics 2018, 7(2), 17; https://doi.org/10.3390/robotics7020017 - 16 Apr 2018
Cited by 31
Abstract
Learning from demonstration (LfD) has been used to help robots to implement manipulation tasks autonomously, in particular, to learn manipulation behaviors from observing the motion executed by human demonstrators. This paper reviews recent research and development in the field of LfD. The main [...] Read more.
Learning from demonstration (LfD) has been used to help robots to implement manipulation tasks autonomously, in particular, to learn manipulation behaviors from observing the motion executed by human demonstrators. This paper reviews recent research and development in the field of LfD. The main focus is placed on how to demonstrate the example behaviors to the robot in assembly operations, and how to extract the manipulation features for robot learning and generating imitative behaviors. Diverse metrics are analyzed to evaluate the performance of robot imitation learning. Specifically, the application of LfD in robotic assembly is a focal point in this paper. Full article
(This article belongs to the Special Issue Feature Papers)
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