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Robotics
Special Issues
10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics
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10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Intelligent Robots and Mechatronics".

Deadline for manuscript submissions: closed (15 November 2021) | Viewed by 42461

Special Issue Editors

Prof. Dr. Giuseppe Carbone

E-Mail Website
Guest Editor
Department of Mechanical, Energy and Management Engineering, Università della Calabria, 87036 Rende, Italy
Interests: robotics; robot design; mechatronics; walking hexapod; design procedure; mechanics of machinery; leg–wheel
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alessandro Di Nuovo

E-Mail Website
Guest Editor
Department of Computing, Sheffield Hallam University, Sheffield S1 1WB, UK
Interests: cognitive robotics; developmental robotics; human–robot interactions; intelligent robots; machine and deep learning applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In 2021, Robotics will be celebrating its 10th anniversary. To date, Robotics has published 400 papers by more than 1300 authors. Over 850 reviewers have submitted at least one review report. We offer our sincerest thanks to our readers, innumerable authors, anonymous peer reviewers, editors, and all others working on the journal who have given their time and efforts over the years. Without your help, Robotics would not be where it is today.

This year will see the 10th anniversary of Robotics. To mark this important milestone, a Special Issue entitled “10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics” is being launched. This Special Issue will collect communications, full papers, and high-quality review papers in the field of intelligent robots and mechatronics.

Topics addressed in this Special Issue include, but are not limited to, the following:

  • Modeling and design strategies;
  • Design solutions and developments;
  • Mechatronic devices and applications;
  • Innovative service tasks;
  • Industrial applications;
  • Sensor integration and experimental testing strategies;
  • Intelligent control and operation strategies;
  • Modular, scalable, wearable robots or devices.

Prof. Dr. Giuseppe Carbone
Dr. Alessandro Di Nuovo
Guest Editors

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 submissions that pass pre-check are 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 monthly 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 1800 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.

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

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Research

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15 pages, 5736 KiB  
Article
A Reconfiguration Algorithm for the Single-Driven Hexapod-Type Parallel Mechanism
by Alexey Fomin, Anton Antonov and Victor Glazunov
Robotics 2022, 11(1), 8; https://doi.org/10.3390/robotics11010008 - 2 Jan 2022
Viewed by 2816
Abstract
This paper presents a hexapod-type reconfigurable parallel mechanism that operates from a single actuator. The mechanism design allows reproducing diverse output link trajectories without using additional actuators. The paper provides the kinematic analysis where the analytical relationships between the output link coordinates and [...] Read more.
This paper presents a hexapod-type reconfigurable parallel mechanism that operates from a single actuator. The mechanism design allows reproducing diverse output link trajectories without using additional actuators. The paper provides the kinematic analysis where the analytical relationships between the output link coordinates and actuated movement are determined. These relations are used next to develop an original and computationally effective algorithm for the reconfiguration procedure. The algorithm enables selecting mechanism parameters to realize a specific output link trajectory. Several examples demonstrate the implementation of the proposed techniques. CAD simulations on a mechanism virtual prototype verify the correctness of the suggested algorithm. Full article
(This article belongs to the Special Issue 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics)
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21 pages, 3595 KiB  
Article
Mechatronic Model of a Compliant 3PRS Parallel Manipulator
by Antonio Ruiz, Francisco J. Campa, Oscar Altuzarra, Saioa Herrero and Mikel Diez
Robotics 2022, 11(1), 4; https://doi.org/10.3390/robotics11010004 - 28 Dec 2021
Cited by 2 | Viewed by 3190
Abstract
Compliant mechanisms are widely used for instrumentation and measuring devices for their precision and high bandwidth. In this paper, the mechatronic model of a compliant 3PRS parallel manipulator is developed, integrating the inverse and direct kinematics, the inverse dynamic problem of the manipulator [...] Read more.
Compliant mechanisms are widely used for instrumentation and measuring devices for their precision and high bandwidth. In this paper, the mechatronic model of a compliant 3PRS parallel manipulator is developed, integrating the inverse and direct kinematics, the inverse dynamic problem of the manipulator and the dynamics of the actuators and the control. The kinematic problem is solved, assuming a pseudo-rigid model for the deflection in the compliant revolute and spherical joints. The inverse dynamic problem is solved, using the Principle of Energy Equivalence. The mechatronic model allows the prediction of the bandwidth of the manipulator motion in the 3 degrees of freedom for a given control and set of actuators, helping in the design of the optimum solution. A prototype is built and validated, comparing experimental signals with the ones from the model. Full article
(This article belongs to the Special Issue 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics)
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21 pages, 6205 KiB  
Article
A Robot Arm Design Optimization Method by Using a Kinematic Redundancy Resolution Technique
by Omar W. Maaroof, Mehmet İsmet Can Dede and Levent Aydin
Robotics 2022, 11(1), 1; https://doi.org/10.3390/robotics11010001 - 22 Dec 2021
Cited by 7 | Viewed by 5573
Abstract
Redundancy resolution techniques have been widely used for the control of kinematically redundant robots. In this work, one of the redundancy resolution techniques is employed in the mechanical design optimization of a robot arm. Although the robot arm is non-redundant, the proposed method [...] Read more.
Redundancy resolution techniques have been widely used for the control of kinematically redundant robots. In this work, one of the redundancy resolution techniques is employed in the mechanical design optimization of a robot arm. Although the robot arm is non-redundant, the proposed method modifies robot arm kinematics by adding virtual joints to make the robot arm kinematically redundant. In the proposed method, a suitable objective function is selected to optimize the robot arm’s kinematic parameters by enhancing one or more performance indices. Then the robot arm’s end-effector is fixed at critical positions while the redundancy resolution algorithm moves its joints including the virtual joints because of the self-motion of a redundant robot. Hence, the optimum values of the virtual joints are determined, and the design of the robot arm is modified accordingly. An advantage of this method is the visualization of the changes in the manipulator’s structure during the optimization process. In this work, as a case study, a passive robotic arm that is used in a surgical robot system is considered and the task is defined as the determination of the optimum base location and the first link’s length. The results indicate the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics)
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19 pages, 6389 KiB  
Article
Feasibility and Performance Validation of a Leap Motion Controller for Upper Limb Rehabilitation
by Marcus R. S. B. de Souza, Rogério S. Gonçalves and Giuseppe Carbone
Robotics 2021, 10(4), 130; https://doi.org/10.3390/robotics10040130 - 4 Dec 2021
Cited by 7 | Viewed by 3595
Abstract
The leap motion controller is a commercial low-cost marker-less optical sensor that can track the motion of a human hand by recording various parameters. Upper limb rehabilitation therapy is the treatment of people having upper limb impairments, whose recovery is achieved through continuous [...] Read more.
The leap motion controller is a commercial low-cost marker-less optical sensor that can track the motion of a human hand by recording various parameters. Upper limb rehabilitation therapy is the treatment of people having upper limb impairments, whose recovery is achieved through continuous motion exercises. However, the repetitive nature of these exercises can be interpreted as boring or discouraging while patient motivation plays a key role in their recovery. Thus, serious games have been widely used in therapies for motivating patients and making the therapeutic process more enjoyable. This paper explores the feasibility, accuracy, and repeatability of a leap motion controller (LMC) to be applied in combination with a serious game for upper limb rehabilitation. Experimental feasibility tests are carried out by using an industrial robot that replicates the upper limb motions and is tracked by using an LMC. The results suggest a satisfactory performance in terms of tracking accuracy although some limitations are identified and discussed in terms of measurable workspace. Full article
(This article belongs to the Special Issue 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics)
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21 pages, 4202 KiB  
Article
A Robot Architecture Using ContextSLAM to Find Products in Unknown Crowded Retail Environments
by Daniel Dworakowski, Christopher Thompson, Michael Pham-Hung and Goldie Nejat
Robotics 2021, 10(4), 110; https://doi.org/10.3390/robotics10040110 - 26 Sep 2021
Cited by 10 | Viewed by 4508
Abstract
Grocery shoppers must negotiate cluttered, crowded, and complex store layouts containing a vast variety of products to make their intended purchases. This complexity may prevent even experienced shoppers from finding their grocery items, consuming a lot of their time and resulting in monetary [...] Read more.
Grocery shoppers must negotiate cluttered, crowded, and complex store layouts containing a vast variety of products to make their intended purchases. This complexity may prevent even experienced shoppers from finding their grocery items, consuming a lot of their time and resulting in monetary loss for the store. To address these issues, we present a generic grocery robot architecture for the autonomous search and localization of products in crowded dynamic unknown grocery store environments using a unique context Simultaneous Localization and Mapping (contextSLAM) method. The contextSLAM method uniquely creates contextually rich maps through the online fusion of optical character recognition and occupancy grid information to locate products and aid in robot localization in an environment. The novelty of our robot architecture is in its ability to intelligently use geometric and contextual information within the context map to direct robot exploration in order to localize products in unknown environments in the presence of dynamic people. Extensive experiments were conducted with a mobile robot to validate the overall architecture and contextSLAM, including in a real grocery store. The results of the experiments showed that our architecture was capable of searching for and localizing all products in various grocery lists in different unknown environments. Full article
(This article belongs to the Special Issue 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics)
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Review

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23 pages, 498 KiB  
Review
Personalization and Localization in Human-Robot Interaction: A Review of Technical Methods
by Mehdi Hellou, Norina Gasteiger, Jong Yoon Lim, Minsu Jang and Ho Seok Ahn
Robotics 2021, 10(4), 120; https://doi.org/10.3390/robotics10040120 - 3 Nov 2021
Cited by 17 | Viewed by 5336
Abstract
Personalization and localization are important when developing social robots for different sectors, including education, industry, healthcare or restaurants. This allows for an adjustment of robot behaviors according to the needs, preferences or personality of an individual when referring to personalization or to the [...] Read more.
Personalization and localization are important when developing social robots for different sectors, including education, industry, healthcare or restaurants. This allows for an adjustment of robot behaviors according to the needs, preferences or personality of an individual when referring to personalization or to the social conventions or the culture of a country when referring to localization. However, there are different models that enable personalization and localization presented in the current literature, each with their advantages and drawbacks. This work aims to help researchers in the field of social robotics by reviewing and analyzing different papers in this domain. We specifically focus our review by exploring different robots that employ distinct models for the adaptation of the robot to its environment. Additionally, we study an array of methods used to adapt the nonverbal and verbal skills of social robots, including state-of-the-art techniques in artificial intelligence. Full article
(This article belongs to the Special Issue 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics)
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28 pages, 1878 KiB  
Review
Reinforcement Learning for Pick and Place Operations in Robotics: A Survey
by Andrew Lobbezoo, Yanjun Qian and Hyock-Ju Kwon
Robotics 2021, 10(3), 105; https://doi.org/10.3390/robotics10030105 - 13 Sep 2021
Cited by 32 | Viewed by 15957
Abstract
The field of robotics has been rapidly developing in recent years, and the work related to training robotic agents with reinforcement learning has been a major focus of research. This survey reviews the application of reinforcement learning for pick-and-place operations, a task that [...] Read more.
The field of robotics has been rapidly developing in recent years, and the work related to training robotic agents with reinforcement learning has been a major focus of research. This survey reviews the application of reinforcement learning for pick-and-place operations, a task that a logistics robot can be trained to complete without support from a robotics engineer. To introduce this topic, we first review the fundamentals of reinforcement learning and various methods of policy optimization, such as value iteration and policy search. Next, factors which have an impact on the pick-and-place task, such as reward shaping, imitation learning, pose estimation, and simulation environment are examined. Following the review of the fundamentals and key factors for reinforcement learning, we present an extensive review of all methods implemented by researchers in the field to date. The strengths and weaknesses of each method from literature are discussed, and details about the contribution of each manuscript to the field are reviewed. The concluding critical discussion of the available literature, and the summary of open problems indicates that experiment validation, model generalization, and grasp pose selection are topics that require additional research. Full article
(This article belongs to the Special Issue 10th Anniversary of Robotics—Feature Papers in Intelligent Robots and Mechatronics)
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