Research

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13 pages, 2095 KiB

Open AccessArticle

Layered-Cost-Map-Based Traffic Management for Multiple AMRs via a DDS

by Seungwoo Jeong, Taekwon Ga, Inhwan Jeong, Jongkyu Oh and Jongeun Choi

Appl. Sci. 2022, 12(16), 8084; https://doi.org/10.3390/app12168084 - 12 Aug 2022

Cited by 1 | Viewed by 1563

A traffic management system can be used to control multiple automated mobile robots (AMRs) effectively. This paper proposes traffic management for multiple AMRs based on a layered cost map in ROS 2 for multiple purposes. Using the layered cost map, the new concepts [...] Read more.

A traffic management system can be used to control multiple automated mobile robots (AMRs) effectively. This paper proposes traffic management for multiple AMRs based on a layered cost map in ROS 2 for multiple purposes. Using the layered cost map, the new concepts of a prohibition filter, lane filter, fleet layer, and region filter are proposed and implemented. The prohibition filter can help a user set an area that would prohibit an AMR from trespassing. The lane filter can help set one-way directions based on an angle image. The fleet layer can help AMRs share their locations via the traffic management server. The region filter requests for or receives an exclusive area, which can be occupied by only one AMR from the traffic management server. Multiple AMRs communicate via a data distribution service (DDS), which is shared by topics in the same DDS domain. The traffic management server in the domain sends or receives topics to each of the AMRs. The experiments of AMRs under the proposed traffic management show the effectiveness of our approach. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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20 pages, 3430 KiB

Open AccessArticle

A Motion Capture and Imitation Learning Based Approach to Robot Control

by Peteris Racinskis, Janis Arents and Modris Greitans

Appl. Sci. 2022, 12(14), 7186; https://doi.org/10.3390/app12147186 - 17 Jul 2022

Cited by 7 | Viewed by 2181

Abstract

Imitation learning is a discipline of machine learning primarily concerned with replicating observed behavior of agents known to perform well on a given task, collected in demonstration data sets. In this paper, we set out to introduce a pipeline for collecting demonstrations and [...] Read more.

Imitation learning is a discipline of machine learning primarily concerned with replicating observed behavior of agents known to perform well on a given task, collected in demonstration data sets. In this paper, we set out to introduce a pipeline for collecting demonstrations and training models that can produce motion plans for industrial robots. Object throwing is defined as the motivating use case. Multiple input data modalities are surveyed, and motion capture is selected as the most practicable. Two model architectures operating autoregressively are examined—feedforward and recurrent neural networks. Trained models execute throws on a real robot successfully, and a battery of quantitative evaluation metrics is proposed. Recurrent neural networks outperform feedforward ones in most respects, but this advantage is not universal or conclusive. The data collection, pre-processing and model training aspects of our proposed approach show promise, but further work is required in developing Cartesian motion planning tools before it is applicable in production applications. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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18 pages, 61249 KiB

Open AccessArticle

Design of the Crawler Units: Toward the Development of a Novel Hybrid Platform for Infrastructure Inspection

by Sergio Leggieri, Carlo Canali and Darwin G. Caldwell

Appl. Sci. 2022, 12(11), 5579; https://doi.org/10.3390/app12115579 - 31 May 2022

Cited by 2 | Viewed by 1826

Abstract

Inspections of industrial and civil infrastructures are necessary to prevent damages and loss of human life. Although robotic inspection is gaining momentum, most of the operations are still performed by human workers. The main limiting factors of inspection robots are the lack of [...] Read more.

Inspections of industrial and civil infrastructures are necessary to prevent damages and loss of human life. Although robotic inspection is gaining momentum, most of the operations are still performed by human workers. The main limiting factors of inspection robots are the lack of versatility as well as the low reliability of these devices, since they need to operate in a non-structured environment. In this work, a novel Hybrid Platform for inspection in industrial contexts is proposed, focusing on the design and testing of the Crawler Unit. The goal is to solve versatility related issues exploiting modularity and self-reconfigurability. The Hybrid Platform consists of three main systems: a mobile Main Base and two Crawler Units. Each would operate independently, accomplishing specific tasks. Docking interfaces, on each device, allow the systems to reconfigure into different robots. The Crawler Unit operates in constrained environments and narrow spaces. The Main Base patrols wide areas and deploys the Crawler Units near the inspection site. For dealing with challenging conditions, the two Crawler Units can dock together, reconfiguring into a snake-like robot. Additionally, once docked to the Main Base, the two Crawlers can operate also as robotic arms, providing manipulation abilities to the platform. The first version of the Crawler Unit exhibited an interesting performance over flat and uneven terrains. To extend the mobility of this robot, a second version was developed, introducing some innovations in the system design. These innovations provided the Crawler Unit with advanced mobility in the vertical plane, thus allowing the robot to deal with more complex scenarios such as crossing gaps, overcoming obstacles and lifting the modules. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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16 pages, 27780 KiB

Open AccessArticle

Design of a Novel Long-Reach Cable-Driven Hyper-Redundant Snake-like Manipulator for Inspection and Maintenance

by Carlo Canali, Alessandro Pistone, Daniele Ludovico, Paolo Guardiani, Roberto Gagliardi, Lorenzo De Mari Casareto Dal Verme, Giuseppe Sofia and Darwin G. Caldwell

Appl. Sci. 2022, 12(7), 3348; https://doi.org/10.3390/app12073348 - 25 Mar 2022

Cited by 8 | Viewed by 2493

Abstract

Robotic inspection and maintenance are gaining importance due to the number of different scenarios in which robots can operate. The use of robotic systems to accomplish such tasks has deep implications in terms of safety for human workers and can significantly extend the [...] Read more.

Robotic inspection and maintenance are gaining importance due to the number of different scenarios in which robots can operate. The use of robotic systems to accomplish such tasks has deep implications in terms of safety for human workers and can significantly extend the life of infrastructures and industrial facilities. In this context, long-reach cable-driven hyper-redundant robots can be employed to inspect areas that are difficult to reach and hazardous environments such as tanks and vessels. This paper presents a novel long-reach cable-driven hyper-redundant robot called SLIM (Snake-Like manipulator for Inspection and Maintenance). SLIM consists of a robotic arm, a pan and tilt mechanism as end-effector, and an actuation box that can rotate and around which the arm can wrap. The robot has a total of 15 degrees of freedom and, therefore, for the task of positioning the tool centre point in a bi-dimensional Cartesian space with a specific attitude, it has 10 degrees of redundancy. The robot is designed to operate in harsh environments and high temperatures and can deploy itself up to about 4.8 m. This paper presents the requirements that drove the design of the robot, the main aspects of the mechanical and electronic systems, the control strategy, and the results of preliminary experimental tests performed with a physical prototype to evaluate the robot performances. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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16 pages, 6461 KiB

Open AccessArticle

Implementation of Robots Integration in Scaled Laboratory Environment for Factory Automation

by Dragiša Mišković, Lazar Milić, Andrej Čilag, Tanja Berisavljević, Achim Gottscheber and Mirko Raković

Appl. Sci. 2022, 12(3), 1228; https://doi.org/10.3390/app12031228 - 25 Jan 2022

Cited by 8 | Viewed by 3984

Abstract

Robotic systems for research and development of factory automation are complex and unavailable for broad deployment in robotic laboratory settings. The usual robotic factory automation setup consists of series of sensors, robotic arms and mobile robots integrated and orchestrated by a central information [...] Read more.

Robotic systems for research and development of factory automation are complex and unavailable for broad deployment in robotic laboratory settings. The usual robotic factory automation setup consists of series of sensors, robotic arms and mobile robots integrated and orchestrated by a central information system. Cloud-based integration has been gaining traction in recent years. In order to build such a system in a laboratory environment, there are several practical challenges that have to be resolved to come to a point when such a system can become operational. In this paper, we present the development of one such system composed of (i) a cloud-based system built on top of open platform for innovation in logistics, (ii) a prototyped mobile robot with a forklift to manipulate pallets in a “factory” floor, and (iii) industrial robot ABB IRB 140 with a customized gripper and various sensors. A mobile robot is designed as an autonomous four Mecanum wheels system with on-board LiDAR and RGB-D sensor for simultaneous localization and mapping. The paper shows a use case of the overall system and highlights the advantages of having a laboratory setting with real robots for the research of factory automation in a laboratory environment. Moreover, the proposed solution could be scaled and replicated in real factory automation applications. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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33 pages, 1409 KiB

Open AccessArticle

Crowdsourced Evaluation of Robot Programming Environments: Methodology and Application

by Daria Piacun, Tudor B. Ionescu and Sebastian Schlund

Appl. Sci. 2021, 11(22), 10903; https://doi.org/10.3390/app112210903 - 18 Nov 2021

Cited by 2 | Viewed by 1785

Abstract

Industrial robot programming tools increasingly rely on graphical interfaces, which aim at rendering the programming task more accessible to a wide variety of users. The usability of such tools is currently being evaluated in controlled environments, such as laboratories or companies, in which [...] Read more.

Industrial robot programming tools increasingly rely on graphical interfaces, which aim at rendering the programming task more accessible to a wide variety of users. The usability of such tools is currently being evaluated in controlled environments, such as laboratories or companies, in which a group of participants is asked to carry out several tasks using the tool and then fill out a standardized questionnaire. In this context, this paper proposes and evaluates an alternative evaluation methodology, which leverages online crowdsourcing platforms to produce the same results as face-to-face evaluations. We applied the proposed framework in the evaluation of a web-based industrial robot programming tool called Assembly. Our results suggest that crowdsourcing facilitates a cost-effective, result-oriented, and reusable methodology for performing user studies anonymously and online. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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19 pages, 19037 KiB

Open AccessArticle

Towards Contactless Learning Activities during Pandemics Using Autonomous Service Robots

by Anas Al Tarabsheh, Maha Yaghi, AbdulRehman Younis, Razib Sarker, Sherif Moussa, Yazeed Eldigair, Hassan Hajjdiab, Ayman El-Baz and Mohammed Ghazal

Appl. Sci. 2021, 11(21), 10449; https://doi.org/10.3390/app112110449 - 07 Nov 2021

Cited by 3 | Viewed by 2210

Abstract

The COVID-19 pandemic has had a significant impact worldwide, impacting schools, undergraduate, and graduate university education. More than half a million lives have been lost due to COVID-19. Moving towards contactless learning activities has become a research area due to the rapid advancement [...] Read more.

The COVID-19 pandemic has had a significant impact worldwide, impacting schools, undergraduate, and graduate university education. More than half a million lives have been lost due to COVID-19. Moving towards contactless learning activities has become a research area due to the rapid advancement of technology, particularly in artificial intelligence and robotics. This paper proposes an autonomous service robot for handling multiple teaching assistant duties in the educational field to move towards contactless learning activities during pandemics. We use SLAM to map and navigate the environment to proctor an exam. We also propose a human–robot voice interaction and an academic content personalization algorithm. Our results show that our robot can navigate the environment to proctor students avoiding any static or dynamic obstacles. Our cheating detection system obtained a testing accuracy of 86.85%. Our image-based exam paper scanning system can scan, extract, and process exams with high accuracy. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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17 pages, 7889 KiB

Open AccessArticle

Autonomous Service Drones for Multimodal Detection and Monitoring of Archaeological Sites

by Adel Khelifi, Gabriele Ciccone, Mark Altaweel, Tasnim Basmaji and Mohammed Ghazal

Appl. Sci. 2021, 11(21), 10424; https://doi.org/10.3390/app112110424 - 05 Nov 2021

Cited by 8 | Viewed by 2265

Abstract

Constant detection and monitoring of archaeological sites and objects have always been an important national goal for many countries. The early identification of changes is crucial to preventive conservation. Archaeologists have always considered using service drones to automate collecting data on and below [...] Read more.

Constant detection and monitoring of archaeological sites and objects have always been an important national goal for many countries. The early identification of changes is crucial to preventive conservation. Archaeologists have always considered using service drones to automate collecting data on and below the ground surface of archaeological sites, with cost and technical barriers being the main hurdles against the wide-scale deployment. Advances in thermal imaging, depth imaging, drones, and artificial intelligence have driven the cost down and improved the quality and volume of data collected and processed. This paper proposes an end-to-end framework for archaeological sites detection and monitoring using autonomous service drones. We mount RGB, depth, and thermal cameras on an autonomous drone for low-altitude data acquisition. To align and aggregate collected images, we propose two-stage multimodal depth-to-RGB and thermal-to-RGB mosaicking algorithms. We then apply detection algorithms to the stitched images to identify change regions and design a user interface to monitor these regions over time. Our results show we can create overlays of aligned thermal and depth data on RGB mosaics of archaeological sites. We tested our change detection algorithm and found it has a root mean square error of 0.04. To validate the proposed framework, we tested our thermal image stitching pipeline against state-of-the-art commercial software. We cost-effectively replicated its functionality while adding a new depth-based modality and created a user interface for temporally monitoring changes in multimodal views of archaeological sites. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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27 pages, 12619 KiB

Open AccessArticle

AI-Powered Service Robotics for Independent Shopping Experiences by Elderly and Disabled People

by Mohammed Ghazal, Maha Yaghi, Abdalla Gad, Gasm El Bary, Marah Alhalabi, Mohammad Alkhedher and Ayman S. El-Baz

Appl. Sci. 2021, 11(19), 9007; https://doi.org/10.3390/app11199007 - 27 Sep 2021

Cited by 6 | Viewed by 3354

Abstract

Through human development and technological expansion, it has become apparent that the potential lies within each individual to have an essential part in the transcendence of society and the community. People less privileged than others may need more strength and determination to surpass [...] Read more.

Through human development and technological expansion, it has become apparent that the potential lies within each individual to have an essential part in the transcendence of society and the community. People less privileged than others may need more strength and determination to surpass their current resources to overcome normal and natural obstacles in order to simulate an environment where productivity and creativity exist. This paper aims to study an approach that will assist the elderly and people of determination in one of the most essential activities practiced by individuals: shopping. The study focuses on facilitating the acquirement of items from shelves and skipping the cashier line. The proposed system is a service robot supported by a robotic arm and a linear actuator as a lifting mechanism, controlled by a remote joystick to help the elderly or disabled people reach items on high shelves. The scanning system is based on barcode detection, using transfer learning. The network was designed using YOLOv2 layers connected to TinyYOLO as feature extraction layers. This network has proven to be the most practical, with 86.4% accuracy and real-time operation with 27 FPS in comparison to using the YOLOv2 layers with DarkNet or VGG19 as feature extraction layers. An anti-theft system is integrated into the robot to improve the reliability of the self-checkout feature. The system uses computer vision GMM and Kalman filter for item detection inside the cart, and the item is validated to be the one that has been scanned, using SURF for structural features, HSV for color, and load-sensors mounted to the base of the cart to measure the item’s weight. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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18 pages, 1423 KiB

Open AccessArticle

Impact of a Robot Manipulation on the Dimensional Measurements in an SPC-Based Robot Cell

by Aleš Zore, Robert Čerin and Marko Munih

Appl. Sci. 2021, 11(14), 6397; https://doi.org/10.3390/app11146397 - 11 Jul 2021

Cited by 3 | Viewed by 1674

Abstract

In our study a robot was used to deliver objects for measurement into the Equator gauging system. To investigate the robot’s manipulation influence on dimensional measurements, the robot’s tasks were divided into basic functions. Based on these basic functions, nine different robot-manipulation scenarios [...] Read more.

In our study a robot was used to deliver objects for measurement into the Equator gauging system. To investigate the robot’s manipulation influence on dimensional measurements, the robot’s tasks were divided into basic functions. Based on these basic functions, nine different robot-manipulation scenarios were defined, i.e., from zero to full robot manipulation, for two measuring objects (named Magnet and PKR) and six measurement characteristics (rectangular and spherical). The robot’s manipulation influence was determined on the basis of the statistical parameters

C_{p}

, R, and the

6 σ

obtained from a measurement system analysis (MSA) type-1 study. The results show that the degree of implemented manipulation of the robot affects the scattering of the measurement data. However, the effect is much more pronounced in the case of length measurements than with spherical geometries. Different measuring methods (touch-triggering or scanning measurement mode, number of sampling points) were used, which showed similar measurement data. This directly indicated the influence of the robot’s manipulation on

C_{p}

, R and

6 σ

. Increasing the degree of the robot’s manipulation decreases the

C_{p}

value and increases the R and

6 σ

values for the length measurements. There is no such pronounced course in the spherical geometries, where the values of

C_{p}

, R and

6 σ

remain approximately the same. The main influential factor for decreasing the

C_{p}

value with increasing robot manipulation was the angular misalignment of the object’s orientation in the fixture. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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16 pages, 5243 KiB

Open AccessArticle

Collaborative Robotics: Enhance Maintenance Procedures on Primary Flight Control Servo-Actuators

by Andrea Raviola, Michele Antonacci, Francesco Marino, Giovanni Jacazio, Massimo Sorli and Gerko Wende

Appl. Sci. 2021, 11(11), 4929; https://doi.org/10.3390/app11114929 - 27 May 2021

Cited by 3 | Viewed by 1856

Abstract

Electro-Hydraulic Servo-Actuators (EHSAs) are mainly used to command primary flight control surfaces in military and commercial aircraft. Since these devices are crucial for vehicle stability and maneuverability, a correct assessment of their health status is mandatory. Within this framework, a joint research project [...] Read more.

Electro-Hydraulic Servo-Actuators (EHSAs) are mainly used to command primary flight control surfaces in military and commercial aircraft. Since these devices are crucial for vehicle stability and maneuverability, a correct assessment of their health status is mandatory. Within this framework, a joint research project (HyDiag), held by Politecnico di Torino and Lufthansa Technik AG (LHT), aims to provide a more efficient and reliable procedure to determine the operating conditions of the EHSA. A smart and automatic sequence, able to extract several health features of the Unit Under Test (UUT), has been developed and integrated. The present paper discusses the implementation of a collaborative robot, equipped with a vision system and customized tools, for both health features extraction, and maintenance tasks on unserviceable servo-actuators. The main challenges related to the automation of such complex tasks in a real working environment are highlighted, togetherwith the advantages brought by the proposed approach. The paper also presents the first results of an ongoing experimental campaign. Specifically, it reports the enhancements of the maintenance procedures using collaborative robotics and possible future developments. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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14 pages, 4559 KiB

Open AccessArticle

A Practical and Effective Layout for a Safe Human-Robot Collaborative Assembly Task

by Leonardo Sabatino Scimmi, Matteo Melchiorre, Mario Troise, Stefano Mauro and Stefano Pastorelli

Appl. Sci. 2021, 11(4), 1763; https://doi.org/10.3390/app11041763 - 17 Feb 2021

Cited by 37 | Viewed by 3623

Abstract

This work describes a layout to carry out a demonstrative assembly task, during which a collaborative robot performs pick-and-place tasks to supply an operator the parts that he/she has to assemble. In this scenario, the robot and operator share the workspace and a [...] Read more.

This work describes a layout to carry out a demonstrative assembly task, during which a collaborative robot performs pick-and-place tasks to supply an operator the parts that he/she has to assemble. In this scenario, the robot and operator share the workspace and a real time collision avoidance algorithm is implemented to modify the planned trajectories of the robot avoiding any collision with the human worker. The movements of the operator are tracked by two Microsoft Kinect v2 sensors to overcome problems related with occlusions and poor perception of a single camera. The data obtained by the two Kinect sensors are combined and then given as input to the collision avoidance algorithm. The experimental results show the effectiveness of the collision avoidance algorithm and the significant gain in terms of task times that the highest level of human-robot collaboration can bring. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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Review

Jump to: Research

20 pages, 5236 KiB

Open AccessReview

Smart Industrial Robot Control Trends, Challenges and Opportunities within Manufacturing

by Janis Arents and Modris Greitans

Appl. Sci. 2022, 12(2), 937; https://doi.org/10.3390/app12020937 - 17 Jan 2022

Cited by 73 | Viewed by 15031

Abstract

Industrial robots and associated control methods are continuously developing. With the recent progress in the field of artificial intelligence, new perspectives in industrial robot control strategies have emerged, and prospects towards cognitive robots have arisen. AI-based robotic systems are strongly becoming one of [...] Read more.

Industrial robots and associated control methods are continuously developing. With the recent progress in the field of artificial intelligence, new perspectives in industrial robot control strategies have emerged, and prospects towards cognitive robots have arisen. AI-based robotic systems are strongly becoming one of the main areas of focus, as flexibility and deep understanding of complex manufacturing processes are becoming the key advantage to raise competitiveness. This review first expresses the significance of smart industrial robot control in manufacturing towards future factories by listing the needs, requirements and introducing the envisioned concept of smart industrial robots. Secondly, the current trends that are based on different learning strategies and methods are explored. Current computer-vision, deep reinforcement learning and imitation learning based robot control approaches and possible applications in manufacturing are investigated. Gaps, challenges, limitations and open issues are identified along the way. Full article

(This article belongs to the Special Issue Smart Robots for Industrial Applications)

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