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The State-of-the-Art of Robotics in Asia

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 17698

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Prof. Dr. Kensuke Harada

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Guest Editor

Graduate School of Engineering Science, Osaka University, Osaka, Japan
Interests: motion planning; machine learning; human motion analysis; motion control robotic hands/gripper in robotic manipulation research
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Shuxiang Guo

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Guest Editor

Intelligent Mechanical Systems Engineering, Faculty of Engineering, Kagawa University, Takamatsu, Japan
Interests: basic research on the micro-machine applied in the biomedical field; research on micro active catheter system for medical support; research and development of the intellectual production and medical welfare robot

Dr. Yunchao Tang

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Guest Editor

College of Urban and Rural Construction, Zhongkai University of Agriculture and Engineering, Guangzhou, China
Interests: computer vision; field robotics; frp composites; recycled concrete; mechanical performance of steel structures; computer vision; 3d reconstruction
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Dr. Mingjie Dong

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Guest Editor

Department of Materials and Manufacturing, Beijing University of Technology, Beijing, China
Interests: rehabilitation robots; mechanism; impedance contron; human-robot interaction
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Prof. Dr. Wei Feng

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Guest Editor

Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen 518055, China
Interests: industrial robots; construction robots; intelligent equipment and industrial internet

Special Issue Information

Dear Colleagues,

Now more than ever, robotics is developing at a much faster pace, both inside and outside industrial environments. Service robotics, surgical and rehabilitation robotics, assistive robotics, and other novel application fields are becoming more and more significant, not only from technological and economical viewpoints, but also in terms of their daily life and social implications. Even the implementation and role of robots in production lines and other traditional frames are being widely revised, since robots are rapidly changing from slave devices to cyber-physical systems in the Industry 4.0 framework. In this context, research concerning robot mechanics, modelling, design, and control is set to play an increasingly central role.

This Special Issue aims to disseminate the latest research achievements, findings, and ideas in the robotics field, with particular attention paid to the Asia scenario. However, manuscripts presenting results of national and international projects with Asiatic partners will also be welcome in this Special Issue.

We welcome you to send a short abstract for feature paper submissions to the Editorial Office (robotics@mdpi.com) before the formal submission of your manuscript. Selected planned papers can be published in full open access form, free of charge if accepted after a peer review.

Prof. Dr. Kensuke Harada
Prof. Dr. Shuxiang Guo
Dr. Yunchao Tang
Dr. Mingjie Dong
Prof. Dr. Wei Feng
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.

Published Papers (10 papers)

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Research

18 pages, 8968 KiB

Open AccessArticle

BIMBot for Autonomous Laser Scanning in Built Environments

by Nanying Liang, Yu Pin Ang, Kaiyun Yeo, Xiao Wu, Yuan Xie and Yiyu Cai

Robotics 2024, 13(2), 22; https://doi.org/10.3390/robotics13020022 - 26 Jan 2024

Viewed by 1406

Abstract

Accurate and complete 3D point clouds are essential in creating as-built building information modeling (BIM) models, although there are challenges in automating the process for 3D point cloud creation in complex environments. In this paper, an autonomous scanning system named BIMBot is introduced, which integrates advanced light detection and ranging (LiDAR) technology with robotics to create 3D point clouds. Using our specially developed algorithmic pipeline for point cloud processing, iterative registration refinement, and next best view (NBV) calculation, this system facilitates an efficient, accurate, and fully autonomous scanning process. The BIMBot’s performance was validated using a case study in a campus laboratory, featuring complex structural and mechanical, electrical, and plumbing (MEP) elements. The experimental results showed that the autonomous scanning system produced 3D point cloud mappings in fewer scans than the manual method while maintaining comparable detail and accuracy, demonstrating its potential for wider application in complex built environments. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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12 pages, 5011 KiB

Open AccessArticle

Genetic Algorithm-Based Data Optimization for Efficient Transfer Learning in Convolutional Neural Networks: A Brain–Machine Interface Implementation

by Goragod Pongthanisorn and Genci Capi

Robotics 2024, 13(1), 14; https://doi.org/10.3390/robotics13010014 - 15 Jan 2024

Viewed by 1446

Abstract

In brain–machine interface (BMI) systems, the performance of trained Convolutional Neural Networks (CNNs) is significantly influenced by the quality of the training data. Another issue is the training time of CNNs. This paper introduces a novel approach by combining transfer learning and a Genetic Algorithm (GA) to optimize the training data of CNNs. Transfer learning is implemented across different subjects, and the data chosen by GA aim to improve CNN performance. In addition, the GA-selected data shed light on the similarity in brain activity between subjects. Two datasets are used: (1) the publicly available BCI Competition IV, in which the subjects performed motor imagery (MI) tasks, and (2) the dataset created by healthy subjects of our laboratory performing motor movement (MO) tasks. The experimental results indicate that the brain data selected by the GA improve the recognition accuracy of the target CNN (TCNN) using pre-trained base CNN (BCNN). The improvement in accuracy is 11% and 4% for the BCI Competition IV and our laboratory datasets, respectively. In addition, the GA-selected training data reduce the CNN training time. The performance of the trained CNN, utilizing transfer learning, is tested for real-time control of a robot manipulator. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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21 pages, 12480 KiB

Open AccessArticle

An Enhanced Multi-Sensor Simultaneous Localization and Mapping (SLAM) Framework with Coarse-to-Fine Loop Closure Detection Based on a Tightly Coupled Error State Iterative Kalman Filter

by Changhao Yu, Zichen Chao, Haoran Xie, Yue Hua and Weitao Wu

Robotics 2024, 13(1), 2; https://doi.org/10.3390/robotics13010002 (registering DOI) - 21 Dec 2023

Viewed by 1534

Abstract

In order to attain precise and robust transformation estimation in simultaneous localization and mapping (SLAM) tasks, the integration of multiple sensors has demonstrated effectiveness and significant potential in robotics applications. Our work emerges as a rapid tightly coupled LIDAR-inertial-visual SLAM system, comprising three tightly coupled components: the LIO module, the VIO module, and the loop closure detection module. The LIO module directly constructs raw scanning point increments into a point cloud map for matching. The VIO component performs image alignment by aligning the observed points and the loop closure detection module imparts real-time cumulative error correction through factor graph optimization using the iSAM2 optimizer. The three components are integrated via an error state iterative Kalman filter (ESIKF). To alleviate computational efforts in loop closure detection, a coarse-to-fine point cloud matching approach is employed, leverging Quatro for deriving a priori state for keyframe point clouds and NanoGICP for detailed transformation computation. Experimental evaluations conducted on both open and private datasets substantiate the superior performance of the proposed method compared to similar approaches. The results indicate the adaptability of this method to various challenging situations. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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12 pages, 3524 KiB

Open AccessArticle

Task-Based Configuration Synthesis of an Underactuated Resilient Robot

by Tan Zhang, Dan Zhang and Wenjun Zhang

Robotics 2023, 12(5), 121; https://doi.org/10.3390/robotics12050121 - 23 Aug 2023

Cited by 3 | Viewed by 1034

Abstract

A resilient robot can recover its original function after partial damage of the system. This paper develops an underactuated resilient robot that utilizes a combination of passive joints, active joints, adjustable links, and passive links. A novel method based on the genetic algorithm was proposed to determine the goal configuration of a partially damaged robot. The novelty of the method lies in the integration of both discrete and continuous variables. This model is illustrated by a 3-DOF robot manipulator in the simulation. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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18 pages, 4445 KiB

Open AccessArticle

A Hybrid Motion Planning Algorithm for Multi-Mobile Robot Formation Planning

by Haojie Chen, Zifan Wang, Xiaoxu Liu, Wenke Ma, Qiang Wang, Wenjun Zhang and Tan Zhang

Robotics 2023, 12(4), 112; https://doi.org/10.3390/robotics12040112 - 04 Aug 2023

Viewed by 1157

Abstract

This paper addresses the problem of relative position-based formation planning for a leader–follower multi-robot setup, where the robots adjust the formation parameters, such as size and three-dimensional orientation, to avoid collisions and progress toward their goal. Specifically, we develop a virtual sub-target-based obstacle avoidance method, which involves a transitional virtual sub-target that guides the robots to avoid obstacles according to obstacle information, target, and boundary. Moreover, we develop a changing formation strategy to determine the necessity to avoid collisions and a priority-based model to determine which robots move, thus dynamically adjusting the relative distance between the followers and the leader. The backstepping-based sliding motion controller guarantees that the trajectory and velocity tracking errors converge to zero. The proposed robot navigation method can be employed in various environments and types of obstacles, allowing for a formation change. Furthermore, it is efficient and scalable under various numbers of robots. The approach is experimentally verified using three real mobile robots and up to five mobile robots in simulated scenarios. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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27 pages, 23361 KiB

Open AccessArticle

Design and Performance Analysis of a Torsional Soft Actuator Based on Hyperelastic Materials

by Zhengyun Xu, Haiqiang Liu, Weihua Feng, Huaming Yang, Xin Nie and Rougang Zhou

Robotics 2023, 12(4), 94; https://doi.org/10.3390/robotics12040094 - 28 Jun 2023

Cited by 1 | Viewed by 1195

Abstract

Conducting research on soft robots is crucial as there are still many problems that need to be resolved in the areas of material selection, structure design and manufacture, and drive control. Soft manipulators, a subset of soft robots, are now a popular area of study for many researchers. In comparison to typical manipulators, soft manipulators feature a high degree of gripping flexibility and a basic morphological structure. They are composed of flexible materials. They have a wide range of potential applications in healthcare, rehabilitation, bionics, and detection, and they can compensate for the drawbacks of rigid manipulators in some use scenarios. A modular soft-body torsional gripping system is developed after a torsional and gripping actuator is conceived and constructed, and its performance examined. The torsion actuator and the grasping actuator can be combined in the system in a modular fashion. With the help of RGB-D vision algorithms, this multi-modular setup makes it possible to combine soft actuators with various twisting degrees and achieve exact gripping. Through pneumatic control, the target object is precisely grasped and rotated at various angles, enabling the rotation of the target object in three dimensions. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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25 pages, 5401 KiB

Open AccessArticle

Finger Joint Stiffness Estimation with Joint Modular Soft Actuators for Hand Telerehabilitation

by Fuko Matsunaga, Shota Kokubu, Pablo Enrique Tortos Vinocour, Ming-Ta Ke, Ya-Hsin Hsueh, Shao Ying Huang, Jose Gomez-Tames and Wenwei Yu

Robotics 2023, 12(3), 83; https://doi.org/10.3390/robotics12030083 - 07 Jun 2023

Cited by 3 | Viewed by 1911

Abstract

In a telerehabilitation environment, it is difficult for a therapist to understand the condition of a patient’s finger joints because of the lack of direct assessment. In particular, not enabling the provision of spasticity evaluation significantly reduces the optimal performance of telerehabilitation. In a previous study, it has been proposed that finger stiffness could be estimated using an analytical model of a whole-finger soft actuator. However, because the whole-finger soft actuators require high air pressure for high bending performance and are costly to customize for each patient, using joint modular soft actuators for telerehabilitation turns to be a necessity, though stiffness estimation with joint modular soft actuators has not been studied yet. Another problem is caused by using a marker-based joint angle measurement, which requires the markers to be attached to the exact positions, and limits its application in telerehabilitation. In this study, we proposed a procedure of finger joint stiffness estimation that combines information acquired from a joint modular soft actuator and a marker-less hand joint position acquisition device. Correction parameters were added to the previous analytical model for -the bending analysis of a joint assisted using a joint modular soft actuator. Moreover, a multi-variate regression model was implemented for correcting joint angles obtained from the hand joint position acquisition device. As a result, a reasonable accuracy of stiffness estimation was achieved for rehabilitation with the joint modular soft actuators, which suggests the possibility of using the proposed method to evaluate the finger spasticity in a telerehabilitation environment. This is a big step forward towards optimal hand telerehabilitation. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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12 pages, 4039 KiB

Open AccessArticle

Based on the Foot–Ground Contact Mechanics Model and Velocity Planning Buffer Control

by Boxuan Zhang, Lichao Wang, Yangwei Wang and Zehao Yuan

Robotics 2023, 12(1), 17; https://doi.org/10.3390/robotics12010017 - 23 Jan 2023

Cited by 1 | Viewed by 1743

Abstract

In order to reduce the impact of the leg joint motors and body electric devices of a falling robot, active flexible control based on force and velocity is proposed. A velocity planning buffer method based on a virtual model is proposed. We established a mechanical model of leg and ground contact. Then, we controlled the knee joint angular velocity change after the robot contacted the ground to reduce the collision impact force and to protect the robot’s joint motors and body’s internal parts. First, the relationship between contact force and velocity was analyzed through the contact mechanical model between leg and ground, and the target was determined. Then, by planning the velocity of the robot’s thigh and hip joint, the velocity mutation during contact was reduced so that the impact on the robot was reduced. This method can avoid complex accurate physics model building and complex torque signal interference filtering processing, the control process is simple and its effectiveness is verified by ADAMS simulation and experimental verification. The velocity planning buffer strategy was tested in experimental studies which showed that the contact force of the buffer strategy was 0.671 times that of no buffer. Additionally, the contact impact acceleration of velocity planning was 1.5505 g, which was less than the force 1.7 g of virtual model control. The velocity planning buffer strategy was better to protect the robot. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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18 pages, 6192 KiB

Open AccessArticle

Graph-Based Framework on Bimanual Manipulation Planning from Cooking Recipe

by Kota Takata, Takuya Kiyokawa, Natsuki Yamanobe, Ixchel G. Ramirez-Alpizar, Weiwei Wan and Kensuke Harada

Robotics 2022, 11(6), 123; https://doi.org/10.3390/robotics11060123 - 11 Nov 2022

Viewed by 1806

Abstract

It is difficult to effectively operate a dual-arm robot using only the information written in a cooking recipe. To cope with this problem, this paper proposes a graph-based approach on bimanual cooking motion planning from a cooking recipe. In our approach, we first decompose the cooking recipe into graph elements. Then, we try to connect the graph elements taking into account the attributes of the input/output nodes. If two graph elements cannot be connected to each other, we search for a graph element that can be inserted between them from a motion database. Since the constructed graph includes the whole sequence of the robot’s motions to perform the cooking task, we can generate a task sequence of a dual-arm manipulator simultaneously performing two different tasks by using two arms. Through experimental study, we show that it is possible to generate robot motions from a cooking recipe and perform the cooking motions while simultaneously moving the left and right arms. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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15 pages, 4665 KiB

Open AccessArticle

Shelf Replenishment Based on Object Arrangement Detection and Collapse Prediction for Bimanual Manipulation

by Tomohiro Motoda, Damien Petit, Takao Nishi, Kazuyuki Nagata, Weiwei Wan and Kensuke Harada

Robotics 2022, 11(5), 104; https://doi.org/10.3390/robotics11050104 - 22 Sep 2022

Cited by 3 | Viewed by 2827

Abstract

Object manipulation automation in logistic warehouses has recently been actively researched. However, shelf replenishment is a challenge that requires the precise and careful handling of densely piled objects. The irregular arrangement of objects on a shelf makes this task particularly difficult. This paper presents an approach for generating a safe replenishment process from a single depth image, which is provided as an input to two networks to identify arrangement patterns and predict the occurrence of collapsing objects. The proposed inference-based strategy provides an appropriate decision and course of action on whether to create an insertion space while considering the safety of the shelf content. In particular, we exploit the bimanual dexterous manipulation capabilities of the associated robot to resolve the task safely, without re-organizing the entire shelf. Experiments with a real bimanual robot were performed in three typical scenarios: shelved, stacked, and random. The objects were randomly placed in each scenario. The experimental results verify the performance of our proposed method in randomized situations on a shelf with a real bimanual robot. Full article

(This article belongs to the Special Issue The State-of-the-Art of Robotics in Asia)

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