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Recent Development and Applications of Remote Robot Systems

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 9606

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Special Issue Editor

Prof. Dr. Yutaka Ishibashi

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Guest Editor

Graduate School of Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan
Interests: QoS control; remote robot systems; haptic communications; networked virtual environments
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In remote robot systems, users can remotely operate robots having various kinds of sensors such as visual, auditory, force, and olfactory sensors. The users can conduct remote cooperative work with robots efficiently and accurately since they are able to watch, hear, touch, and/or smell through the corresponding interface devices/displays in applications where the following kinds of robots play active parts: Medical robots which operate sophisticated surgery and robots which assist rehabilitation, working robots in outer space, deep sea, and reactor decommissioning, where humans cannot enter easily, and rescue robots and drones which help victims of disasters such as earthquakes and concentrated heavy rains and deliver shortage (e.g., foods, water, and clothes) to them.

This special issue focuses on recent development and applications of remote robot systems. By using the systems, we can largely enhance abilities of robots and humans because we can conduct various types of work which only humans cannot do or only robots cannot do. However, when sensed information is transmitted over a network like the Internet, the quality and stability may seriously degraded owing to network delay, delay jitter, and packet loss. Especially, by using multiple systems, the problems may become complicated; for example, change from bilateral control to multilateral control may lead to instability phenomena. To realize stable and high-quality control in the remote robot systems, we need to solve a variety of problems by using QoS (Quality of Service) control, stabilization control, AI technologies, and so on. This special issue invites submissions on, but not limited to, the above research areas.

Prof. Dr. Yutaka Ishibashi
Guest Editor

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Keywords

remote robot control
cooperation between humans and robots, and supports by humans to robots and vice versa
industrial robots, mobile robots, unmanned aerial vehicles (uav), and autonomous robots
sensors and displays
force feedback
bilateral/multilateral control
stabilization control
quality of Service (QoS) control
quality of Experience (QoE) management
artificial intelligence (AI)

Published Papers (4 papers)

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Research

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15 pages, 4919 KiB

Open AccessArticle

Autonomous, Digital-Twin Free Path Planning and Deployment for Robotic NDT: Introducing LPAS: Locate, Plan, Approach, Scan Using Low Cost Vision Sensors

by Alastair Poole, Mark Sutcliffe, Gareth Pierce and Anthony Gachagan

Appl. Sci. 2022, 12(10), 5288; https://0-doi-org.brum.beds.ac.uk/10.3390/app12105288 - 23 May 2022

Cited by 5 | Viewed by 1929

Abstract

Robotised Non Destructive Testing (NDT) presents multifaceted advantages, saving time and reducing repetitive manual workloads for highly skilled Ultrasonic Testing (UT) operators. Due to the requisite accuracy and reliability of the field, robotic NDT has traditionally relied on digital twins for complex path planning procedures enabling precise deployment of NDT equipment. This paper presents a multi-scale and collision-free path planning and implementation methodology enabling rapid deployment of robotised NDT with commercially available sensors. Novel algorithms are developed to plan paths over noisy and incomplete point clouds from low-cost sensors without the need for surface primitives. Further novelty is introduced in online path corrections utilising laser and force feedback while applying a Conformable-Wedge probe UT sensor. Finally, a novel source of data beneficial to automated NDT is introduced by collecting frictional forces of the surface informing the operator of the surface preparation quality. The culmination of this work is a new path-planning free, single-shot automated process removing the need for complex operator-driven procedures with a known surface, visualising collected data for the operator as a three-dimensional C-scan model. The dynamic robotic control enables a move to the industry 4.0 model of adaptive online path planning. Experimental results indicate the flexible and streamlined pipeline for robotic deployment, and demonstrate intuitive data visualisation to aid highly skilled operators in a wide field of industries. Full article

(This article belongs to the Special Issue Recent Development and Applications of Remote Robot Systems)

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20 pages, 2084 KiB

Open AccessArticle

Remote-Controlled Method with Force and Visual Assists Based on Time to Collision for Mobile Robot

by Ryo Masaki, Masato Kobayashi and Naoki Motoi

Appl. Sci. 2022, 12(8), 3727; https://0-doi-org.brum.beds.ac.uk/10.3390/app12083727 - 07 Apr 2022

Cited by 2 | Viewed by 1555

Abstract

Various remote-controlled methods have been developed to improve operability using force or visual assists; however, using only force or visual assists may deteriorate the operability or safety performance. Therefore, a remote-controlled method with both force and visual assists is proposed to improve the operability while maintaining safety performance. The proposed remote-controlled system consists of a wheeled mobile robot, control device, and monitor. The force assist is generated using the time to collision (TTC), which is the predicted time of collision of the mobile robot against an obstacle. This force assist is applied to the operator using a control device to achieve collision avoidance. Using a visual assist, a predicted trajectory for the mobile robot based on the TTC is generated. For operability improvement, this predicted trajectory with color gradation is shown on the monitor. In summary, the achievement of operability improvement while maintaining safety performance is confirmed from experimental results using the proposed method. Full article

(This article belongs to the Special Issue Recent Development and Applications of Remote Robot Systems)

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27 pages, 4482 KiB

Open AccessArticle

A Study on Design and Control of the Multi-Station Multi-Container Transportation System

by Nguyen Huu Loc Khuu, Van Anh Pham, Tran Thanh Cong Vu, Vu Thanh Binh Dao, Thuy Duy Truong, Ngoc Phi Nguyen and Tuong Quan Vo

Appl. Sci. 2022, 12(5), 2686; https://0-doi-org.brum.beds.ac.uk/10.3390/app12052686 - 04 Mar 2022

Cited by 2 | Viewed by 1950

Abstract

In considering the problem of saving spaces during the transportation of items from one station to another, for example, in warehouses, factories, hospitals, etc., an automatic transportation system (ATS) that could take advantage of the above ceiling spaces for the transportation of products is considered. Such a system guarantees that the activities occurring in the floor area will be maintained as usual. To achieve this requirement, the ceiling spaces of a building are used to construct an automatic multi-station multi-container (MSMC) transportation system. This system can transport items from one place to another in the whole system. This system is designed to utilize the spaces above the ceiling, and it has the advantage of saving floor space for transportation operations. This will increase the operational capability of the industries and also improve the productivity of the industry in which this system is implemented. The entire transportation system includes (1) the essential conveying system (which is a functional conveyor module with a specified number of containers); (2) the control block that can monitor and operate the system; and (3) the sensor block for detecting and identifying the containers. The content of this article focuses on the introduction of the mechanical system (1); the control system (2); and the operating principle of the whole system (3). Full article

(This article belongs to the Special Issue Recent Development and Applications of Remote Robot Systems)

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Review

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18 pages, 4076 KiB

Open AccessReview

Sim–Real Mapping of an Image-Based Robot Arm Controller Using Deep Reinforcement Learning

by Minoru Sasaki, Joseph Muguro, Fumiya Kitano, Waweru Njeri and Kojiro Matsushita

Appl. Sci. 2022, 12(20), 10277; https://0-doi-org.brum.beds.ac.uk/10.3390/app122010277 - 12 Oct 2022

Cited by 4 | Viewed by 2572

Abstract

Models trained with Deep Reinforcement learning (DRL) have been deployed in various areas of robotics with varying degree of success. To overcome the limitations of data gathering in the real world, DRL training utilizes simulated environments and transfers the learned policy to real-world scenarios, i.e., sim–real transfer. Simulators fail to accurately capture the entire dynamics of the real world, so simulation-trained policies often fail when applied to reality, termed a reality gap (RG). In this paper, we propose a search (mapping) algorithm that takes in real-world observation (images) and maps them to the policy-equivalent images in the simulated environment using a convolution neural network (CNN) model. The two-step training process, DRL policy and a mapping model, overcomes the RG problem with simulated data only. We evaluated the proposed system with a gripping task of a custom-made robot arm in the real world and compared the performance against a conventional DRL sim–real transfer system. The conventional system achieved a 15–57% success rate in gripping operation depending on the position of the target object while the mapping-based sim–real system achieved 100%. The experimental results demonstrated that the proposed DRL with mapping method appropriately corresponded the real world to the simulated environment, confirming that the scheme can achieve high sim–real generalization at significantly low training costs. Full article

(This article belongs to the Special Issue Recent Development and Applications of Remote Robot Systems)

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