Smart Robot Research Articles

Edge Robotics: Edge-Computing-Accelerated Multirobot Simultaneous Localization and Mapping

With the wide penetration of smart robots in multifarious fields, the simultaneous localization and mapping (SLAM) technique in robotics has attracted growing attention in the community. Yet collaborating SLAM over multiple robots still remains challenging due to performance contradiction between the intensive graphics computation of SLAM and the limited computing capability of robots. While traditional solutions resort to the powerful cloud servers acting as an external computation provider, we show by real-world measurements that the significant communication overhead in data offloading prevents its practicability to real deployment. To tackle these challenges, this article promotes the emerging edge-computing paradigm into multirobot SLAM and proposes RecSLAM, a multirobot laser SLAM system that focuses on accelerating the map construction process under the robot–edge–cloud architecture. In contrast to the conventional multirobot SLAM that generates graphic maps on robots and completely merges them on the cloud, RecSLAM develops a hierarchical map fusion technique that directs robots’ raw data to edge servers for real-time fusion and then sends to the cloud for global merging. To optimize the overall pipeline, an efficient multirobot SLAM collaborative processing framework is introduced to adaptively optimize robot-to-edge offloading tailored to heterogeneous edge resource conditions, meanwhile ensuring the workload balancing among the edge servers. Extensive evaluations show RecSLAM can achieve up to 39.31% processing latency reduction over the state of the art. Besides, a proof-of-concept prototype is developed and deployed in real scenes to demonstrate its effectiveness.

Multi-Tasking Robot using Microcontroller for Agriculture Application

With innovations in every field of our lives, agricultural field also gets impacted by technological innovations on a huge scale. Agriculture is the backbone of India. In order to support this, a multi-functioning robot is required. Smart farming aids in boosting the quality and quantity of the yields. Currently, smart agriculture is implemented to save the manpower and time of work with the help of multitasking robots. This is the advanced booming technology in the agriculture sector. However, certain considerations and approaches should be taken when designing these types of robots, taking into account the agricultural setting in which they will be used. The main aim of this research is to provide smart farming at low cost without compromising on the efficiency of the processes involved. This paper discusses the design procedure and development of an independent multitasking robot that could be applied for agricultural purpose like soil digging, sowing seeds, harvesting as well as irrigation. This robot works on solar energy and will also help in conserving non-renewable energy resources on a large scale thereby contributing towards the sustainability of our planet. With help of technologies, this idea kindles the knowledge in developing more intelligent and smart robots for the agriculture activities.

Polymer-based electronics that can learn to drive: That’s smart

In a recent paper published in <i>Science Advances</i> by Krauhausen and co-authors,¹ the Gkoupidenis' research group from the Max Planck Institute for Polymer Research demonstrated the use of organic neuromorphic electronics to drive a small robot through a maze. Using organic electrochemical transistors (OECTs), the authors designed a neuromorphic circuit and demonstrated energy efficient and reliable learning capabilities enabled by the mixed ionic-electronic conduction of the organic semiconductor. The work demonstrates unprecedented capabilities in organic neuromorphics toward effective local and decentralized learning, which is attractive for smart robotics.

Digitization from the perspective of hotel managers and guests

Bu araştırmada, otel işletmelerindeki akıllı teknolojilere ve robotlara ilişkin otel yöneticilerinin ve otel misafirlerinin bakış açısının belirlenmesi amaçlanmaktadır. Araştırmada nitel araştırma yöntemi tekniklerinden görüşme yoluyla veriler elde edilmiştir. Araştırmada kolayda örneklem yöntemi kullanılmış ve Kuşadası’nda faaliyet gösteren 5 yıldızlı 10 otel işletmesindeki 15 Aralık 2021- 5 Ocak 2022 tarihleri arasında konaklayan 20 otel misafiri ve çalışan 30 otel yöneticisi dâhil edilmiştir. Bulgular, otel yöneticilerinin her ne kadar akıllı teknolojilerin ve robotların otellerde kullanımının birçok avantaj sağlayacağını düşünse de robot iş arkadaşları ile çalışmak istemediğini göstermektedir. Otel misafirleri robotlar konusunda hem olumlu hem de olumsuz duygulara sahip olsa da farklı deneyim yaşamak için robotların hizmet verdiği bir otelde konaklamaya olumlu bakmaktadırlar. Ayrıca otel misafirleri akıllı teknoloji kullanımının misafir memnuniyetini ve hizmet kalitesini olumlu yönde etkileyeceğine inanmaktadırlar.

The implementation and performance evaluation for a smart robot with edge computing algorithms

PurposeApart from, the smart edge computing (EC) robot (SECR) provides the tools to manage Internet of things (IoT) services in the edge landscape by means of real-world test-bed designed in ECR. Eventually, based on the results from two experiments held in little constrained condition, such as the maximum data size is 2GB, the performance of the proposed techniques demonstrate the effectiveness, scalability and performance efficiency of the proposed IoT model.Design/methodology/approachCertainly, the proposed SECR is trying primarily to take over other traditional static robots in a centralized or distributed cloud environment. One aspect of representation of the proposed edge computing algorithms is due to challenge to slow down the consumption of time which happened in an artificial intelligence (AI) robot system. Thus, the developed SECR trained by tiny machine learning (TinyML) techniques to develop a decentralized and dynamic software environment.FindingsSpecifically, the waste time of SECR has actually slowed down when it is embedded with Edge Computing devices in the demonstration of data transmission within different paths. The TinyML is applied to train with image data sets for generating a framework running in the SECR for the recognition which has also proved with a second complete experiment.Originality/valueThe work presented in this paper is the first research effort, and which is focusing on resource allocation and dynamic path selection for edge computing. The developed platform using a decoupled resource management model that manages the allocation of micro node resources independent of the service provisioning performed at the cloud and manager nodes. Besides, the algorithm of the edge computing management is established with different path and pass large data to cloud and receive it. In this work which considered the SECR framework is able to perform the same function as that supports to the multi-dimensional scaling (MDS).

The Fourth Industrial Revolution - Smart Technology, Artificial Intelligence, Robotics and Algorithms: Industrial Psychologists in Future Workplaces.

In the Fourth Industrial Revolution (4IR), STARA (smart technology, artificial intelligence, robotics, and algorithms) is predicted to replace a third of the jobs that exist today. Almost twice as many current work tasks will be handled by robots. It is forecast that by 2025, 85 million jobs may be displaced by a shift in the division of labor between humans and machines, while 97 million new roles may emerge that are more adapted to the new division of labor between humans, machines and algorithms. Industrial psychologists are playing an increasingly important role in the workplace due to these trends from a strategic intelligence perspective. The objective of this article is to present a critical review of industrial psychologists in future workplaces in the context of the 4IR - STARA. A competence model is posed for industrial psychologists to perform a strategic intelligence role in organizations in the 4IR.

Flexible Pressure Sensor With Wide Linear Sensing Range for Human–Machine Interaction

Flexible pressure sensors hold great potential for applications in human–machine interaction and flexible robotics, but the balance of their sensitivity and sensing range remains a challenge. Here, we proposed a flexible piezoresistive pressure sensor based on poly (3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT: PSS) and cross interlocked nylon fabrics. The sensor exhibited a wide sensing range (~1.5 mPa), a low detection limit (6 Pa), a fast response time (less than 40 ms), and an excellent cycling stability (at least 16 000 cycles without any decay). The excellent performance is attributed to the fact that the cross interlocked structure can form a mechanically stable and three-dimensional (3D) sensitive conductive network which allowed a contact area of the pressure sensor to vary continuously, resulting in an extremely large pressure sensing range. In addition, the sensor array system was successfully fabricated and integrated with a rank scanning circuit to achieve mapping and identification of spatial pressure distribution. Finally, we have built and demonstrated a sensing system capable of wireless real-time gesture interaction with a robot. These results provide a new direction for the fabrication of high-performance sensors with tremendous applications for healthcare, wearable electronics, electronic skin, and smart robots.

AUTONOMOUS ROBOTIC SYSTEMS FOR PIPE INSPECTION USING MAPPING AND NONDESTRUCTIVE TESTING

This paper presents the development of a mapping and nondestructive technique (NDT) for the assessment of concrete pipeline networks. It focuses on the inspection of open-end culverts and storm drain systems using sensor networks. The network consists of 3D Lidar/3D camera/radar with NDT sensors. These sensors are mounted on autonomous vehicles that are set to reduce the extent of human operator involvement through intelligent control algorithms. More accurate remote monitoring is achieved by using smart robots and sensor networks equipped with advanced AI-based techniques. In the systems, ground robots are used with onboard sensing to enable environmental observation. The ground robots have the capability of remote communication, teleoperation, and the transmission of collected data. Effective automated mapping requires the flexibility to allow real-time changes in planning to accommodate unmodeled/unexpected uncertainties and disturbances. The autonomous system can be used repeatedly with reduced cost, primarily for maintenance. In addition, making the process autonomous can reduce the risk to human inspectors and save time during inspections. Also, it can be operated by personnel who require less training to obtain the data than standard inspection processes. The developed technology is demonstrated by actual field and lab testing. It provides accurate assessment tools for underground pipeline networks.

Smartphone-based Robot Design Training with Voice Control for Senior High School in Tasikmalaya City

The main objective of this work is to provide training to build smart phone-based smart robots with voice control to teachers at Senior High Schools, Tasikmalaya City, Indonesia. This robot consists of various electronic components such as Arduino, IC L293D, Bluetooth Module HC05, dynamo, gear box and battery. In addition, we have used several software to build intelligent robots such as Arduino software for uploading a command and AMR voice application for controlling via voice commands. The results showed that the teachers had succeeded in making robots with voice control for forward and backward commands with the help of the AMR voice application. In addition, the results of this training are expected to increase the creativity of teachers in the learning process and as teaching materials to create an active and collaborative class.

A Robot Platform for Highly Efficient Pollutant Purification

In this study, we propose a highly efficient robot platform for pollutant adsorption. This robot system consists of a flapping-wing micro aircraft (FWMA) for long-distance transportation and delivery and cost-effective multifunctional Janus microrobots for pollutant purification. The flapping-wing micro air vehicle can hover for 11.3 km with a flapping frequency of approximately 15 Hz, fly forward up to 31.6 km/h, and drop microrobots to a targeted destination. The Janus microrobot, which is composed of a silica microsphere, nickel layer, and hydrophobic layer, is used to absorb the oil and process organic pollutants. These Janus microrobots can be propelled fast up to 9.6 body lengths per second, and on-demand speed regulation and remote navigation are manageable. These Janus microrobots can continuously carry oil droplets in aqueous environments under the control of a uniform rotating magnetic field. Because of the fluid dynamics induced by the Janus microrobots, a highly efficient removal of Rhodamine B is accomplished. This smart robot system may open a door for pollutant purification.

A self-protective piezoelectric-piezoresistive dual-mode device with superior dynamic-static mechanoresponse and energy harvesting performance enabled by flextensional transduction

Dual-mode pressure sensors capable to perceive various external dynamic and static mechanical stimulus are constantly required to develop wearable electronics and smart subhuman robots. However, most sensors can hardly exhibit robust and reliable highly sensitive response to dynamic and static mechanical stimulus coming from rough or cuspidal surfaces. Here, we report a self-protective piezoelectric-piezoresistive dual-mode pressure sensor based on elastic cylinder induced flextensional transduction due to the positive Poisson effect. The cylindric design allows the transition from normal force to lateral expansion force, avoiding direct contact with rough or cuspidal surfaces and endowing the sensor with self-protective characteristic. Surprisingly, the flextensional transduction can give rise to more than 10 times amplification of the normal force to lateral expansion force, contributing to significantly enhanced sensitivity of the piezoresistive and piezoelectric response. Meanwhile, the open circuit voltage, short circuit current and power density of the device can reach up to 200 V, 8 μA and ~82 μW/cm2, enlightening people to design high-performance piezoelectric energy harvesting devices. In addition, the dual-mode device exhibits great potentials for dynamic-static pressure detection and sports evaluation. The proposed flextensional transduction strategy provides people great inspirations to design self-protective sensing devices with dynamic-static mechanoresponse for more complex application scenarios.

Towards the Sign Function Best Approximation for Secure Outsourced Computations and Control

Homomorphic encryption with the ability to compute over encrypted data without access to the secret key provides benefits for the secure and powerful computation, storage, and communication of resources in the cloud. One of its important applications is fast-growing robot control systems for building lightweight, low-cost, smarter robots with intelligent brains consisting of data centers, knowledge bases, task planners, deep learning, information processing, environment models, communication support, synchronous map construction and positioning, etc. It enables robots to be endowed with secure, powerful capabilities while reducing sizes and costs. Processing encrypted information using homomorphic ciphers uses the sign function polynomial approximation, which is a widely studied research field with many practical results. State-of-the-art works are mainly focused on finding the polynomial of best approximation of the sign function (PBAS) with the improved errors on the union of the intervals [−1,−ϵ]∪[ϵ,1]. However, even though the existence of the single PBAS with the minimum deviation is well known, its construction method on the complete interval [−1,1] is still an open problem. In this paper, we provide the PBAS construction method on the interval [−1,1], using as a norm the area between the sign function and the polynomial and showing that for a polynomial degree n≥1, there is (1) unique PBAS of the odd sign function, (2) no PBAS of the general form sign function if n is odd, and (3) an uncountable set of PBAS, if n is even.

Designs of human–robot interaction using depth sensor-based hand gesture communication for smart material-handling robot operations

With rapid developments in biometric recognition, a great deal of attention is being paid to robots which interact smartly with humans and communicate certain types of biometrical information. Such human–machine interaction (HMI), also well-known as human–robot interaction (HRI), will, in the future, prove an important development when it comes to automotive manufacturing applications. Currently, hand gesture recognition-based HRI designs are being practically used in various areas of automotive manufacturing, assembly lines, supply chains, and collaborative inspection. However, very few studies are focused on material-handling robot interactions combined with hand gesture communication of the operator. The current work develops a depth sensor-based dynamic hand gesture recognition scheme for continuous-time operations with material-handling robots. The proposed approach properly employs the Kinect depth sensor to extract features of Hu moment invariants from depth data, through which feature-based template match hand gesture recognition is developed. In order to construct continuous-time robot operations using dynamic hand gestures with concatenations of a series of hand gesture actions, the wake-up reminder scheme using fingertip detection calculations is established to accurately denote the starting, ending, and switching timestamps of a series of gesture actions. To be able to perform typical template match on continuous-time dynamic hand gesture recognition with the ability of real-time recognition, representative frame estimates using centroid, middle, and middle-region voting approaches are also presented and combined with template match computations. Experimental results show that, in certain continuous-time periods, the proposed complete hand gesture recognition framework can provide a smooth operation for the material-handling robot when compared with robots controlled using only extractions of full frames; presented representative frames estimated by middle-region voting will maintain fast computations and still reach the competitive recognition accuracy of 90.8%. The method proposed in this study can facilitate the smart assembly line and human–robot collaborations in automotive manufacturing.

Laser-carbonized MXene/ZiF-67 nanocomposite as an intermediate layer for boosting the output performance of fabric-based triboelectric nanogenerator

The investigation of efficient research approaches to boost the output performance of triboelectric nanogenerators (TENGs) is crucial in extending their practical use in daily life. In this study, a laser-carbonized (LC) MXene/ZiF-67 nanocomposite-based intermediate layer is introduced to achieve outstanding output performance in both contact and non-contact mode (CNM) TENGs. The porous structure of the LC-MXene/ZiF-67 nanocomposite layer contains a high charge density, thereby enabling the surface charges to be conserved for longer periods, and simultaneously increasing the surface potential. Different ratios of MXene/ZiF-67, laser powers, and laser speeds were explored and optimized to improve the output performance of the CNM-TENG. Under optimal conditions, the intermediate and charge generating layer significantly enhanced the contact-TENG output power density of 65 W/m2 at a load resistance of 1.3 MΩ. In addition, the noncontact TENG provided a high charge density of 15.3 µC/m2 and stable output performance at a distance of 2 cm. Finally, demonstrations of the optimized CNM-TENG-based human gait analysis, automobile vehicles, smart robots were presented to enable obstacle detection and human motion alerts, touchless wearable keyboards for security, and self-powered electronic devices. The findings of this study offer an innovative and effective strategy for designing devices with excellent performance for use in self-powered electronic devices and sensing systems.

Insights into the relationship between usability and willingness to use a robot in the future workplaces: Studying the mediating role of trust and the moderating roles of age and STARA.

Background and aimHuman–robot collaboration is the key component of the fourth industrial revolution concept. Workers’ willingness to collaborate with industrial robots is a basic requirement for an efficient and effective interaction. The roles of human-robot trust and technology affinity as mediators in the relationship between robot usability and worker willingness were analyzed in this study. As other critical variables, the mediator roles of Age and STARA were also calculated.Materials and methodsThis study included 400 workers from a car company who interacted with industrial robots in their daily work activities. After examining the questionnaires’ validity and reliability, the main variables were determined to be willingness to use robots and robot usability. AMOS software also considered human-robot trust and worker technology affinity as mediators. The bootstrapping method was used to evaluate indirect relationships. A set of goodness-of-fit indices were presented to determine the adequacy of the goodness of fit between the proposed model and the data.ResultsBased on model fit indices, an overall satisfactory model fit was obtained for the direct/indirect relationship between robot usability and worker willingness to use it (with mediating role of human-robot trust). Workers’ age and fear of Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA) were identified as moderators in the relationship between usability and willingness.ConclusionAttention to the robot usability and the role of workers’ trust in robots appears to be required to ensure workers’ willingness to use robots and the success of human-robot collaboration in future workplaces. As the workers age and their fear of robots grows, usability can play a larger role in increasing their willingness to put robots to work.

AUTONOMOUS ROBOTIC SYSTEMS FOR PIPE INSPECTION USING MAPPING AND NONDESTRUCTIVE TESTING

This paper presents the development of a mapping and nondestructive technique (NDT) for the assessment of concrete pipeline networks. It focuses on the inspection of open-end culverts and storm drain systems using sensor networks. The network consists of 3D Lidar/3D camera/radar with NDT sensors. These sensors are mounted on autonomous vehicles that are set to reduce the extent of human operator involvement through intelligent control algorithms. More accurate remote monitoring is achieved by using smart robots and sensor networks equipped with advanced AI-based techniques. In the systems, ground robots are used with onboard sensing to enable environmental observation. The ground robots have the capability of remote communication, teleoperation, and the transmission of collected data. Effective automated mapping requires the flexibility to allow real-time changes in planning to accommodate unmodeled/unexpected uncertainties and disturbances. The autonomous system can be used repeatedly with reduced cost, primarily for maintenance. In addition, making the process autonomous can reduce the risk to human inspectors and save time during inspections. Also, it can be operated by personnel who require less training to obtain the data than standard inspection processes. The developed technology is demonstrated by actual field and lab testing. It provides accurate assessment tools for underground pipeline networks.

Workforce and Workplace Ecosystem – Challenges and Opportunities in the Age of Digital Transformation and 4IR

Abstract We are witnessing the Fourth Industrial Revolution (4IR) in which technological discoveries and changes are coming at a dizzying speed generating tremendous transformations of organizations, the environment and societies. The purpose of the present paper is to analyze a set of challenges and opportunities of the workforce and workplace ecosystems in the context of 4IR. Innovation – as key ingredient of scaling-up processes – and the widespread implementation of specific 4IR technologies will lead to substantial, sometimes even disruptive changes of the labor market, but also to the workforce and workplace ecosystems’ transformation. Among others, artificial intelligence (AI), smart robotics, and intelligent automation are emerging technologies that dramatically change the ways of work, productivity, but also the types and number of available jobs. This paper has a few specific objectives: summarizing the main technologies and tools specific to 4IR and Industry 4.0; analyzing the major shifts related to the current structure of the workforce -highlighting the external and technological component (AI, robots, automation); analyzing the hybrid workplace (physical and digital); identifying some emerging technologies and their impact on the work ecosystem. The methodology of the study relies on qualitative methods - literature review, systematization of knowledge, observation/ participation (as experts in different national and international consultancy and training programs). The paper draws conclusions and some remarks regarding the intention to address other challenging subjects in the future, such as: rethinking performance management systems to reflect and tackle these challenges; skill gaps and the role of emerging technologies in supporting Society 5.0. - a more sustainable, inclusive and human-centric society.

Droplets in underlying chemical communication recreate cell interaction behaviors

The sensory-motor interaction is a hallmark of living systems. However, developing inanimate systems with “recognize and attack” abilities remains challenging. On the other hand, controlling the inter-droplet dynamics on surfaces is key in microengineering and biomedical applications. We show here that a pair of droplets can become intelligently interactive (chemospecific stimulus-response inter-droplet autonomous operation) when placed on a nanoporous thin film surface. We find an attacker-victim-like non-reciprocal interaction between spatially separated droplets leading to an only-in-one shape instability that triggers a drop projection to selectively couple, resembling cellular phenomenologies such as pseudopod emission and phagocytic-like functions. The nanopore-driven underlying communication and associated chemical activity are the main physical ingredients behind the observed behavior. Our results reveal that basic features found in many living cell types can emerge from a simple two-droplet framework. This work is a promising step towards the design of microfluidic smart robotics and for origin-of-life protocell models.

A Textile Proximity/Pressure Dual-Mode Sensor Based on Magneto-Straining and Piezoresistive Effects

The demand for flexible tactile sensors with both contact and contactless sensing capabilities is growing rapidly in the fields of smart robotics and prosthesis. However, it is still a challenge to integrate high performance proximity and pressure sensing functions in one sensor through simple fabrication process. Here, we propose a textile-based dual-mode sensor that can work on both magneto-straining mode (proximity) and piezoresistive mode (pressure). The sensor is simply fabricated by coating two functional materials in a concentric pattern, i.e., a magnetic layer followed by a conductive layer made of 2D MXene composite, on spandex substrate. As the dual-mode sensor approaches to a magnetic object, the attractive magnetic force will stretch the magnetic layer, along with the conductive layer. The strained conductive layer causes an increase of the resistance. Upon contact, the magnetic force reaches its maximum, while the pressure force works against the magnetic force and starts to reduce the strain of the conductive layer, leading to a decrease of the resistance. The turning point of the resistance can be used to identify the contact moment, and as an indicator of the switching of the two working modes of the sensor. Benefitting from the superior conductivity of the MXene material in the conductive layer, high sensitivity for both proximity sensing (13.76 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> ) and pressure sensing (0.7 kPa <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup> ) was achieved. The proposed dual-mode sensing methodology has great potential in human-machine interaction (HMI) applications.

Highly Elastic Melamine Graphene/MWNT Hybrid Sponge for Sensor Applications

The rapidly increased interest in multifunctional nanoelectronic devices, such as wearable monitors, smart robots, and electronic skin, motivated many researchers toward the development of several kinds of sensors in recent years. Flexibility, stability, sensitivity, and low cost are the most important demands for exploiting stretchable or compressible strain sensors. This article describes the formation and characteristics of a flexible, low-cost strain sensor by combining a commercial melamine sponge and a graphene/carbon nanotubes hybrid. The composite that emerged by doping the highly elastic melamine sponge with a highly conductive graphene/carbon nanotubes hybrid showed excellent piezoresistive behavior, with low resistivity of 22 kΩ m. Its function as a piezoresistive material exhibited a high sensitivity of 0.050 kPa−1 that combined with a wide detection area ranging between 0 to 50 kPa.