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Special Issue "New Trends in Robotics and Automation"

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A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 30 November 2023 | Viewed by 4074

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Special Issue Editors

Prof. Dr. Jian Wu
E-Mail Website
Guest Editor

School of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China
Interests: human-vehicle cooperative steering control; intelligent vehicle motion control; advanced control theory
Special Issues, Collections and Topics in MDPI journals

Dr. Xiangkun He
E-Mail Website
Guest Editor

School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
Interests: reinforcement learning; multi-objective optimization; robust decision and control; autonomous driving and robotics

Dr. Guangfei Xu
E-Mail Website
Guest Editor

School of Mechanical and Automotive Engineering, Liaocheng University, Liaocheng 252000, China
Interests: reinforcement learning; autonomous driving

Special Issue Information

Dear Colleagues，

Robotics and automation technologies have been widely leveraged in diverse domains such as agriculture, healthcare, and transportation, and they have had significant societal impacts and benefits. As robotics and automation technologies play a central role in leading the fourth industrial revolution, new trends in robotics and automation should be thoroughly investigated to enable their development in the long run. With the rapid development of emerging technologies such as artificial intelligence (AI), digital twins (DT), Internet of Things (IoT) and human-computer interaction (HCI), there must be a booming room for robotics and automation to be discussed. Therefore, this Special Issue is proposed here to provide a forum for researchers and practitioners to exchange their latest theoretical and engineering achievements. This special issue aims to compile the latest research and development advances in robotics and automation. The topics of interest within the scope of this special issue include (although not limited to) the following:

Intelligent control in robotics;
Intelligent connected vehicles;
Trustworthy artificial intelligence;
Artificial intelligence technology applied in intelligence system;
Modeling and control of human-machine system;
System state information acquisition and parameter identification;
Application of linear and nonlinear analysis and control;
Decision-making and control with multi-source information;
Decision-making and control for multi-agent system.

Prof. Dr. Jian Wu
Dr. Xiangkun He
Dr. Guangfei Xu
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. Machines 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 2000 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.

Keywords

new theories and studies in robotics
advanced control strategies
control decision-making with multi-source information
artificial intelligence (AI) technology applied in vehicles
system state information acquisition and parameter identification
intelligent connected vehicles
strategy and control of multi-agent cooperative operation
application of linear nonlinear analysis and control
modeling and control of human–machine cooperation

Published Papers (6 papers)

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Research

Open AccessArticle

Visual Place Recognition in Changing Environments with Sequence Representations on the Distance-Space Domain

Ioannis Tsampikos Papapetros

Ioannis Kansizoglou

Loukas Bampis

and

Antonios Gasteratos

Machines 2023, 11(5), 558; https://doi.org/10.3390/machines11050558 - 16 May 2023

Viewed by 309

Abstract

Navigating in a perpetually changing world can provide the basis for numerous challenging autonomous robotic applications. With a view to long-term autonomy, visual place recognition (vPR) systems should be able to robustly operate under extreme appearance changes in their environment. Typically, the utilized data representations are heavily influenced by those changes, negatively affecting the vPR performance. In this article, we propose a sequence-based technique that decouples such changes from the similarity estimation procedure. This is achieved by remapping the sequential representation data into the distance-space domain, i.e., a domain in which we solely consider the distances between image instances, and subsequently normalize them. In such a way, perturbations related to different environmental conditions and embedded into the original representation vectors are avoided, therefore the scene recognition efficacy is enhanced. We evaluate our framework under multiple different instances, with results indicating a significant performance improvement over other approaches. Full article

(This article belongs to the Special Issue New Trends in Robotics and Automation)

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Open AccessArticle

Deep Reinforcement Learning-Based Torque Vectoring Control Considering Economy and Safety

and

Machines 2023, 11(4), 459; https://doi.org/10.3390/machines11040459 - 06 Apr 2023

Viewed by 507

Abstract

This paper presents a novel torque vectoring control (TVC) method for four in-wheel-motor independent-drive electric vehicles that considers both energy-saving and safety performance using deep reinforcement learning (RL). Firstly, the tire model is identified using the Fibonacci tree optimization algorithm, and a hierarchical torque vectoring control scheme is designed based on a nonlinear seven-degree-of-freedom vehicle model. This control structure comprises an active safety control layer and a torque allocation layer based on RL. The active safety control layer provides a torque reference for the torque allocation layer to allocate torque while considering both energy-saving and safety performance. Specifically, a new heuristic random ensembled double Q-learning RL algorithm is proposed to calculate the optimal torque allocation for all driving conditions. Finally, numerical experiments are conducted under different driving conditions to validate the effectiveness of the proposed TVC method. Through comparative studies, we emphasize that the novel TVC method outperforms many existing related control results in improving vehicle safety and energy savings, as well as reducing driver workload. Full article

(This article belongs to the Special Issue New Trends in Robotics and Automation)

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Open AccessArticle

Design and Experiment of Apple Foam Net Sleeve Packaging Machine with Posture Adjustment Function

and

Machines 2023, 11(4), 436; https://doi.org/10.3390/machines11040436 - 29 Mar 2023

Viewed by 615

Abstract

Background: In this study, an apple foam net packing machine is designed to improve the efficiency of apple foam net packing, reduce the intensity of manual work, and meet the market demand for diverse forms of apple packing. Methods: Based on the analysis of apple shape characteristics, a secondary posture adjustment method for apples with a vertical posture adjustment mechanism and a side posture adjustment mechanism is proposed. Based on the observation of human hand-set nets and the analysis of the mechanical characteristics of nets, a dual-system net opening method combining a net slackening system and a net opening system is proposed. Results: The experiment shows that: the apple foam net sleeve packing machine can reach 99% of the apple’s posture adjustment rate, the net opening rate can reach 99%, and the packing rate can reach 98.10%. The packing speed is 10 s/pcs, and the packing efficiency is 355–365 pcs/h. The length of the fused mesh net sleeve is mainly distributed between 138 and 143 mm, which accounts for approximately 80% of the total number of samples. Conclusions: The apples packed by this machine are neatly packaged according to specifications. It can improve the efficiency of apple foam net sleeve packing and replace manual work. Full article

(This article belongs to the Special Issue New Trends in Robotics and Automation)

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Open AccessArticle

Path Tracking Control of Commercial Vehicle Considering Roll Stability Based on Fuzzy Linear Quadratic Theory

and

Machines 2023, 11(3), 382; https://doi.org/10.3390/machines11030382 - 13 Mar 2023

Viewed by 502

Abstract

Commercial vehicles generally drive at a higher speed on structured expressways, and their higher center of mass leads to a lower rollover threshold and a greater rollover risk while steering. Therefore, the design of a lateral trajectory-tracking control strategy for commercial vehicles should not only consider the accuracy of trajectory tracking but also consider roll stability. Based on this control objective, a fuzzy linear quadratic controller was designed in this study to ensure rolling stability in the path-tracking control process and improve the adaptability of the strategy to the driving scenario. Firstly, a steering and braking cooperative control model based on the four-degree-of-freedom model and the multi-point preview model was established. Then, a path tracking controller considering roll stability was designed based on the linear quadratic theory. On this basis, a fuzzy linear quadratic controller was designed to realize the online optimization of cost function weights. Finally, the effectiveness of the control strategy was verified using co-simulation and hardware-in-loop experiments. The results show that the designed controller can effectively adjust the weight of path-tracking and stability according to the vehicle’s state. This effectively improves the vehicle’s control distribution problem. Full article

(This article belongs to the Special Issue New Trends in Robotics and Automation)

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Open AccessArticle

An LWPR-Based Method for Intelligent Lower-Limb Prosthesis Control by Learning the Dynamic Model in Real Time

and

Machines 2023, 11(2), 186; https://doi.org/10.3390/machines11020186 - 30 Jan 2023

Viewed by 627

Abstract

A significant number of people in the world suffer from limb losses, while prosthesis is the hopeful way to help the amputees back to normal life. Recently, the most popular control method used in intelligent prosthesis is FSM-IC (finite state machine with impedance control), which requires a significant amount of manual parameter adjustments to achieve a good model compensation in a discrete way. Taking the lower-limb prosthesis as the research object, this paper applies an LWPR (locally weighted projection regression) model to learn the dynamic model of a prosthesis in real time in order to achieve a better model compensation in a continuous way and propose scientific experimental schemes to verify the control method. First, the basic control framework of lower-limb prosthesis is given. Then, the control law is derived on the basis of model building and LWPR’s addition. Finally, the proper experimental schemes are designed to carry out the control method effectively in a safe way. The experimental results show that the control law with the LWPR model can greatly improve the tracking performance during the swing phase and obtain rather good compliance during the stance phase. Moreover, the results also indicate that the LWPR model can approximate the dynamic model online. This method is hoped to be extended to more applications and fields. Full article

(This article belongs to the Special Issue New Trends in Robotics and Automation)

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Open AccessArticle

Narrow Tilting Vehicle Drifting Robust Control

and

Machines 2023, 11(1), 90; https://doi.org/10.3390/machines11010090 - 10 Jan 2023

Cited by 1 | Viewed by 679

Abstract

The narrow tilting vehicle receives extensive public attention because of traffic congestion and environmental pollution, and the active rolling motion control is a traffic safety precaution that reduces the rollover risk caused by the structure size of the narrow vehicle. The drifting motion control reflects the relatively updated attentive research of the regular-size vehicle, which can take full advantage of the vehicle’s dynamic performance and improve driving safety, especially when tires reach their limits. The narrow tilting vehicle drifting control is worthy of research to improve the driving safety of the narrow tilting vehicle, especially when tires reach the limit. The nonlinear narrow tilting vehicle dynamic model is established with the UniTire model to describe the vehicle motion characteristics and is simplified to reduce the computation of the drifting controller design. The narrow tilting vehicle drifting controller is designed based on the robust theory with uncertain external disturbances. The controller has a wide application, validity, and robustness and whose performance is verified by realizing different drifting motions with different initial driving motions. The narrow tilting vehicle drifting robust control has some practical and theoretical significance for more research. Full article

(This article belongs to the Special Issue New Trends in Robotics and Automation)

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Special Issue "New Trends in Robotics and Automation"

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