Robotic Modules Research Articles

A New Configuration Method for Glass Substrate Transfer Robot Modules Based on Kansei Engineering

How to effectively match the relationship between users’ perceptual demands and the characteristics of industrial robot modules becomes a pressing issue when perceptual demands become a significant determinant of whether users purchase and employ industrial robots. In this regard, we propose a Kansei Engineering-based method for industrial robot module configuration, using the module design of a glass substrate transfer robot as an example. First, the method analyzes the perceptual demand characteristics of the target user, utilizing the semantic difference method, and then establishes a mapping relationship between the user’s perceptual demand and the robot design elements, utilizing the hierarchical inference method. On the basis of this mapping relationship, the robot module for transfer glass substrates is then designed. Finally, orthogonal design and conjoint analysis were used to effectively and objectively analyze user preferences for various module configuration alternatives. The results indicate that the industrial robot’s shape, color, and material are the three appearance characteristics that influence the user’s perceptual demands. The slender, rigid design features of the industrial robot, such as the streamlined drive shaft, lengthwise expanded body structure, integrated body structure, and hidden plugs, as well as the simple color scheme and smooth metal surface, are key elements in the industrial robot’s perceptual design. The turn shaft module and lift shaft module have respective weights of 35.040% and 31.120%, determining whether the glass substrate transfer robot can create a simple style. In the context of the widespread use of industrial robot modules, the methods and findings of this study offer new ideas for the design of industrial robot modules and broaden the research and applications of Kansei Engineering in module design.

A Tensegrity-Based Inchworm-Like Robot for Crawling in Pipes With Varying Diameters

Most current in-pipe robots are usually designed for pipes of a specific size. In this letter, we propose a novel inchworm-like in-pipe robot based on the concept of tensegrity for moving in pipes with varying diameters. Firstly, a tensegrity-based robotic module capable of two kinds of shape change is designed. One kind is extension in the axial direction accompanied by contraction in the radial direction, which is the basis for the wave-like crawling movement of the in-pipe robot. The other kind is expansion in the radial direction while keeping changeless in the axial direction, enabling the module adaptable to pipes with different diameters. Then, the geometrical equilibrium configuration of the tensegrity module is determined, followed by kinematic analysis using force density method. By cascading three modules, the in-pipe crawling robot is developed. Finally, a series of experiments are performed to test the shape changeability and friction force of the tensegrity module, and the mobility, load capacity, and adaptability of the in-pipe robot. The results validate that the robot can crawl in horizontal pipes, vertical pipes, and elbow pipes under the control of a simple actuation sequence. Furthermore, the robot has the abilities to adapt to pipes with different diameters varying from 100 mm to 180 mm. It is suggested that the usage of tensegrity structures brings about higher adaptability, flexibility, and mobility to the in-pipe crawling robot.

Home-Based Robotic Upper Limbs Cardiac Telerehabilitation System.

This article proposes a new, improved home-based cardiac telerehabilitation system enhanced by a robotic and Virtual Reality module for cardiac patients to be used in their rehabilitation program. In this study, a novel strategy was used to integrate existing equipment and applications with newly developed ones, with the aim of reducing the need for technical skills of patients using remote control. Patients with acute or chronic heart diseases require long-term, individualized rehabilitation in order to promote their motor recovery and maintain an active and independent lifestyle. This will be accomplished by creating a system for at-home cardiac telerehabilitation augmented by a VR and cobot systems, which can be used long-term at home by each individual patient. In the pre-feasibility study carried out on healthy volunteers familiar with software applications and robotic systems, we demonstrate that RoboTeleRehab could be technically feasible both hardware and software.

TNT Loss: A Technical and Nontechnical Generative Cooperative Energy Loss Detection System.

This paper describes an electricity technical/nontechnical loss detection method capable of loss type identification, classification, and location. Several technologies are implemented to obtain that goal: (i) an architecture of three generative cooperative AI modules and two additional non-cooperative AI modules for data knowledge sharing is proposed, (ii) new expert consumption-based knowledge of feature collaboration of the entire consumption data are embedded as features in an AI classification algorithm, and (iii) an anomaly pooling mechanism that enables one-to-one mapping of signatures to loss types is proposed. A major objective of the paper is an explanation of how an exact loss type to signature mapping is obtained simply and rapidly, (iv) the role of the reactive energy load profile for enhancing signatures for loss types is exemplified, (v) a mathematical demonstration of the quantitative relationship between the features space to algorithm performance is obtained generically for any algorithm, and (vi) a theory of “generative cooperative modules” for technical/nontechnical loss detection is located and mapped to the presented system. The system is shown to enable high-accuracy technical/nontechnical loss detection, especially differentiated from other grid anomalies that certainly exist in field conditions and are not tagged in the universal datasets. The “pooling” architecture algorithm identifies all other loss types, and a robotic process automation module obtains loss type localization. The system feeds from the entire smart metering data, not only the energy load profile. Other solutions, such as a stand-alone algorithm, have difficulty in obtaining low false positive in field conditions. The work is tested experimentally to demonstrate the matching of experiment and theory.

The Didactic Configuration of a Flexible Manufacturing Cell for the Military APC Building Industry by Implementing the RRTR-Type Modular Serial Robot

Abstract In the present scientific paper, the author aims to highlight the principle design of a flexible manufacturing cell composed of several modules/workstations (degreasing, priming, painting, varnishing to which that of technical quality control is added), in order to process APC hulls, a cell that is to be serviced by a serial-modular industrial robot that will aim to maneuver the benchmarks to the devices of the technological operations to be carried out within it. The following aspects will be analyzed in stages: determining the working space of the robot included in the system by using geometric modeling, determining the speeds and accelerations related to the robot modules needed to handle benchmarks by using kinematic modeling, configuring the cell and determining its cost and that of the robot included in the system.

ROMERIN: A new concept of a modular autonomous climbing robot

Climbing robots play an essential role in performing inspection work in civil infrastructures. These tasks require autonomous robots with competitive costs and the ability to adapt to different types of environments. This article presents ROMERIN, a new concept of a modular legged climbing robot where each leg is an autonomous robotic module in terms of processing capacity, control, and energy. The legs are equipped with suction cups that allow the robot to adhere to different types of surfaces. The proposed design allows the creation of climbing robots with a different number of legs to perform specific inspection tasks. Although each of the legs acts as an independent robot, they have the ability to share information and energy. The proposed control concept enables the development of climbing robots with the ability to adapt to different types of inspection tasks and with resilience characteristics. This article includes a description of the mechatronic design, the kinematics of the seven degree-of-freedom robotic legs, including the adhesion system, and the architecture of the control and simulation system. Finally, we present experimental results to test the modularity concept, mechanical design, and electronics using a four-legged robot configuration. We analyze the performance of the gripping system in different situations on four different surfaces and the behavior of the control architecture for two different robot body trajectories.

Penerapan Modul Pengendali Sistem Robotik Berbasis STEM di Sekolah Menengah Kejuruan

This research is motivated by the lack of learning resources for Robotic System Control subjects and the learning model used is still teacher-centered. This Robotic System Control subject is still a new subject in the 2013 curriculum, so teachers only use learning modules that already exist on the internet without using learning models. Besides, students do not have additional learning resources other than the modules that have been given by the teacher. This study aims to develop a Robotic System Control module using a valid, practical and effective STEM Learning Model. This type of research is the research and development method. The method used is a 4-D model consisting of the stages of definition (Define), design (Design), development (Development) and deployment (Dessiminate). The research subjects were students of class XI TEI SMKN 1 West Sumatra. The data collection technique used an evaluation sheet in the form of a questionnaire for validity and practicality data. while objective tests were used for effectiveness data. The results showed that (1) the validity test of the Robotic System Controller module using the STEM learning model had been tested and declared valid. (2) the practicality test of the Robotic System Controller module using the STEM learning model has been tested and declared practical. (3) testing the effectiveness of the Robotic System Control module using the STEM learning model has been tested and declared effective. Based on the results of the study, it can be concluded that the development of the Robotic System Control module using the STEM learning model is valid, practical, and effective so that it is feasible to use.

Design, Analysis, and Real-Time Simulation of a 3D Soft Robotic Snake.

Snakes are a remarkable source of inspiration for mobile search-and-rescue robots. Their unique slender body structure and multiple modes of locomotion are well-suited to movement in narrow passages and other difficult terrain. The design, manufacturing, modeling, and control techniques of soft robotics make it possible to imitate the structure, mechanical properties, and locomotion gaits of snakes, opening up new possibilities in robotics research. Building on our track record of contributions in this area, this article presents a soft robotic snake made of modules that can actively deform in three-dimensional (3D) and rigorously studies its performance under a range of conditions, including gait parameters, number of modules, and differences in the environment. A soft 3D-printed wave spring sheath is developed to support the robot modules, increasing the snake's performance in climbing steps threefold. Finally, we introduce a simulator and a numerical model to provide a real-time simulation of the soft robotic snake. With the help of the real-time simulator, it is possible to develop and test new locomotion gaits for the soft robotic snake within a short period of time, compared with experimental trial and error. As a result, the soft robotic snake presented in this article is able to locomote on different surfaces, perform different bioinspired and custom gaits, and climb over steps.

AI-Based Soft Module for Safe Human-Robot Interaction towards 4D Printing.

Soft robotic modules have potential use for therapeutic and educational purposes. To do so, they need to be safe, soft, smart, and customizable to serve individuals’ different preferences and personalities. A safe modular robotic product made of soft materials, particularly silicon, programmed by artificial intelligence algorithms and developed via additive manufacturing would be promising. This study focuses on the safe tactile interaction between humans and robots by means of soft material characteristics for translating physical communication to auditory. The embedded vibratory sensors used to stimulate touch senses transmitted through soft materials are presented. The soft module was developed and verified successfully to react to three different patterns of human–robot contact, particularly users’ touches, and then communicate the type of contact with sound. The study develops and verifies a model that can classify different tactile gestures via machine learning algorithms for safe human–robot physical interaction. The system accurately recognizes the gestures and shapes of three-dimensional (3D) printed soft modules. The gestures used for the experiment are the three most common, including slapping, squeezing, and tickling. The model builds on the concept of how safe human–robot physical interactions could help with cognitive and behavioral communication. In this context, the ability to measure, classify, and reflect the behavior of soft materials in robotic modules represents a prerequisite for endowing robotic materials in additive manufacturing for safe interaction with humans.

Analysing an Interactive Problem-Solving Task Through the Lens of Double Stimulation

Problem-solving activities have been studied from a diversity of epistemological perspectives. In problem-solving activities, the initial tensions of a problematic situation led to a cognitive dissonance between conflicting motives and instruments to reach the activity goal. We analyze problem-solving in the continuation of Sannino and Laitinen’s (2015) approach to the analysis of a decision-forming apparatus. The originality of this study is in consideration of the materialistic nature of double stimulation that appears during the activity of the CreaCube problem-solving task. This activity engages the participant in solving tasks with interactive robotic instruments. To solve a task, the subject is required to build interactive robotic modules into a specific configuration which will cause the artifact to move from an initial position to a predetermined final position. The conflict of stimuli in the CreaCube is strong and observable because of the tangibility of the artifact, which is manipulated by the participant into different configurations with the goal of solving the task. We discuss double stimulation in relation to the artifactual interactive affordances of educational robotics.

Analysis of Dynamic Behavior of ParReEx Robot Used in Upper Limb Rehabilitation

This paper presents a dynamic analysis of the ParReEx multibody mechanism, which has been designed for human wrist joint rehabilitation. The starting point of the research is a virtual prototype of the ParReEx multibody mechanism. This model is used to simulate the dynamics of the multibody mechanism using ADAMS in three simulation scenarios: (a) rigid kinematic elements without friction in joints, (b) rigid kinematic elements with friction in joints, and (c) kinematic elements as deformable solids with friction in joints. In all three cases, the robot is used by a virtual patient in the form of a mannequin. Results such as the connecting forces in the kinematic joints and the torques necessary to operate the ParReEx robot modules are obtained by dynamic simulation in MSC.ADAMS. The torques obtained by numerical simulation are compared with those obtained experimentally. Finite element structural optimization (FEA) of the flexion/extension multibody mechanism module is performed. The results demonstrate the operational safety of the ParReEx multibody mechanism, which is structurally capable of supporting the external loads to which it is subjected.

Three-dimensional auxetic structure design methods based on bulking-induced deformation and the application in soft crawling robot

The 3D auxetic buckling pattern in the compression process is used to design auxetic structures. However, obtaining this pattern is time consuming and unintentional. In this paper, three auxetic structures, namely, globally deformed cross-frustum (GC) structure, partially deformed cross-frustum (PC) structure, and core deformed cross-frustum (CC) structure are proposed on the basis of the 3D auxetic deformation equation. The GC structure and PC structure can stably realize the 3D auxetic property through finite element analysis and experimental verification of structures. The structural strength of the latter structure is 2–5 times greater than that of the former structure. The CC structure exhibits a 3D auxetic property during the entire compression process and has excellent structural strength, which is greater than that of the first two structures. The rotational pattern can be also realized by the CC structure within the specified parameter range.A soft crawling robot with a motion module and perception module is designed by using the proposed auxetic structures. The motion module of the soft robot is designed by using the GC structure, and the perception module is realized by using the CC structure. The combination of modules can realize different functions, including advancement and rotation. The robot can be rapidly fabricated by digital light processing and has potential application value in medical treatment and other fields.

Autonomous Driving Control Based on the Perception of a Lidar Sensor and Odometer

Recently, many artificial intelligence applications in smart cars have been utilized in real life. Making an unmanned ground vehicle (UGV) capable of moving autonomously has become a critical topic. Hence, in this work, a novel method for a UGV to realize path planning and obstacle avoidance is presented using a deep deterministic policy gradient approach (DDPG). More specifically, the lidar sensor mounted on the vehicle is utilized to measure the distance between the vehicle and the surrounding obstacles, and the odometer measures the mileage of the vehicle for the purpose of estimating the current location. Then, the above sensed data are treated as the training data for the DDPG training procedure, and several experiments are performed in different settings utilizing the robot operating system (ROS) and the Gazebo simulator with a real robot module, TurtleBot3, to present a comprehensive discussion. The simulation results show that using the presented design and reward architecture, the DDPG method is better than the classic deep Q-network (DQN) method, e.g., taking fewer steps to reach the goal, less training time to find the smallest number of steps for reaching the goal, and so on.

Non-motorised Rehabilitation Device for Performance Assessment in Upper Limb Stroke Rehabilitation: A Pilot Study

Stroke patients with upper limb disability restricted to carry out their activities of daily living. The patient needs a motivation to recover from a stroke and the patient also needs to go through a rehabilitation process at the same time. The conventional rehabilitation process scoring systems are always subjective, lack reliability and relies heavily on the ability of the trained physiotherapist that providing only rough estimates on motor function. On the other hand, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. Therefore, a simple non-motorized device was developed as a tool to objectively assess hand function of stroke patients. This study was carried out to investigate the suitability of using thedeveloped device with stroke patient populations and to evaluate the performance of clinical scores prediction of the stroke patients. A total of five patients with upper limb disability following stroke consented to take part in this study. Twelve predictive variables were investigated, relating to the total movement time, velocity, strategy, accuracy, and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. The hardware for measuring elbow angle hasbeen developed to measurethe shoulder movement performedby patient during the assessment process. In addition to that, the shoulder movement calculation method has been proposed and validated.The findings indicatethat the performance of prediction for all assessment modules hasbeen increased after implementing the shoulder movement calculation. It is recommended this calculation method to be used in conjunction with kinematic variables to carry out the data acquisition process in the future for improvement of effectiveness and accuracy of the robotic assessment.

Review of the Standard and Advanced Screening, Staging Systems and Treatment Modalities for Cervical Cancer.

Simple SummaryThis review discusses the timeline and development of the recommended screening tests, diagnosis system, and therapeutics implemented in clinics for precancer and cancer of the uterine cervix. The incorporation of the latest automation, machine learning modules, and state-of-the-art technologies into these aspects are also discussed.Cancer arising from the uterine cervix is the fourth most common cause of cancer death among women worldwide. Almost 90% of cervical cancer mortality has occurred in low- and middle-income countries. One of the major aetiologies contributing to cervical cancer is the persistent infection by the cancer-causing types of the human papillomavirus. The disease is preventable if the premalignant lesion is detected early and managed effectively. In this review, we outlined the standard guidelines that have been introduced and implemented worldwide for decades, including the cytology, the HPV detection and genotyping, and the immunostaining of surrogate markers. In addition, the staging system used to classify the premalignancy and malignancy of the uterine cervix, as well as the safety and efficacy of the various treatment modalities in clinical trials for cervical cancers, are also discussed. In this millennial world, the advancements in computer-aided technology, including robotic modules and artificial intelligence (AI), are also incorporated into the screening, diagnostic, and treatment platforms. These innovations reduce the dependence on specialists and technologists, as well as the work burden and time incurred for sample processing. However, concerns over the practicality of these advancements remain, due to the high cost, lack of flexibility, and the judgment of a trained professional that is currently not replaceable by a machine.

A Proprioceptive Soft Robot Module Based on Supercoiled Polymer Artificial Muscle Strings.

In this paper, a multi-functional soft robot module that can be used to constitute a variety of soft robots is proposed. The body of the soft robot module made of rubber is in the shape of a long strip, with cylindrical chambers at both the top end and bottom end of the module for the function of actuators and sensors. The soft robot module is driven by supercoiled polymer artificial muscle (SCPAM) strings, which are made from conductive nylon sewing threads. Artificial muscle strings are embedded in the chambers of the module to control its deformation. In addition, SCPAM strings are also used for the robot module’s sensing based on the linear relationship between the string’s length and their resistance. The bending deformation of the robot is measured by the continuous change of the sensor’s resistance during the deformation of the module. Prototypes of an inchworm-like crawling robot and a soft robotic gripper are made, whose crawling ability and grasping ability are tested, respectively. We envision that the proposed proprioceptive soft robot module could potentially be used in other robotic applications, such as continuum robotic arm or underwater robot.

Self-Assembly and Self-Repair during Motion with Modular Robots

Self-reconfigurable modular robots consist of multiple modular elements and have the potential to enable future autonomous systems to adapt themselves to handle unstructured environments, novel tasks, or damage to their constituent elements. This paper considers methods of self-assembly, bringing together robotic modules to form larger organism-like structures, and self-repair, removing and replacing faulty modules damaged by internal events or environmental phenomena, which allow group tasks for the multi-robot organism to continue to progress while assembly and repair take place. We show that such “in motion” strategies can successfully assemble and repair a range of structures. Previously developed self-assembly and self-repair strategies have required group tasks to be halted before they could begin. This paper finds that self-assembly and self-repair methods able to operate during group tasks can enable faster completion of the task than previous strategies, and provide reliability benefits in some circumstances. The practicality of these new methods is shown with physical hardware demonstrations. These results show the feasibility of assembling and repairing modular robots whilst other tasks are in progress.

Snake Robot Gripper Module for Search and Rescue in Narrow Spaces

This letter presents a gripper module for a snake-like robot to perform search and rescue tasks in a narrow space. The proposed gripper module has three features: (1) It can accommodate the fingers inside its body. (2) It has three fingers that can grip objects with irregular surfaces stably. (3) One of the fingers is equipped with a camera on the fingertip to search in a narrow space. To implement the above features in a small, light, and compact gripper module, we propose a novel design of a gripper module with three fingers and eight degrees of freedom. The joint configuration of the proposed gripper is unique compared with a general-type gripper. A prototype of the proposed gripper module has been integrated into a snake-like robot to demonstrate its capability of performing rescue tasks in a collapsed environment. The three features of the proposed gripper module are experimentally verified: it is light (0.4 kg), small (less than 68 mm in diameter), and powerful (grasping force = 2.48kgf).

IoT and AI-Based Application for Automatic Interpretation of the Affective State of Children Diagnosed with Autism.

In the context in which it was demonstrated that humanoid robots are efficient in helping children diagnosed with autism in exploring their affective state, this paper underlines and proves the efficiency of a previously developed machine learning-based mobile application called PandaSays, which was improved and integrated with an Alpha 1 Pro robot, and discusses performance evaluations using deep convolutional neural networks and residual neural networks. The model trained with MobileNet convolutional neural network had an accuracy of 56.25%, performing better than ResNet50 and VGG16. A strategy for commanding the Alpha 1 Pro robot without its native application was also established and a robot module was developed that includes the communication protocols with the application PandaSays. The output of the machine learning algorithm involved in PandaSays is sent to the humanoid robot to execute some actions as singing, dancing, and so on. Alpha 1 Pro has its own programming language—Blockly—and, in order to give the robot specific commands, Bluetooth programming is used, with the help of a Raspberry Pi. Therefore, the robot motions can be controlled based on the corresponding protocols. The tests have proved the robustness of the whole solution.

Development of a Soft Robotics Module for Active Control of Sitting Comfort.

Sitting comfort is an important factor for passengers in selecting cars, airlines, etc. This paper proposes a soft robotic module that can be integrated into the seat cushion to provide better comfort experiences to passengers. Building on rapid manufacturing technologies and a data-driven approach, the module can be controlled to sense the applied force and the displacement of the top surface and actuate according to four designed modes. A total of 2 modules were prototyped and integrated into a seat cushion, and 16 subjects were invited to test the module’s effectiveness. Experiments proved the principle by showing significant differences regarding (dis)comfort. It was concluded that the proposed soft robotics module could provide passengers with better comfort experiences by adjusting the pressure distribution of the seat as well as introducing a variation of postures relevant for prolonged sitting.