Simple Robotic System Research Articles

A spray-cooling based antagonistic SMA actuator (SCASA) with low resistance consumption and high driving frequency

Owing to the large strain output and high power-to-weight ratio, using temperature-induced shape memory alloy (SMA) springs in the form of antagonistic actuators offers the opportunity to develop simple, lightweight, and multi-mode robotic systems. Currently, the capabilities and deep application of these robotic systems are hindered by the relatively large resistance consumption and limited driving frequency of the antagonistic SMA actuators, primarily attributed to the cooling rate of SMA. In this paper, a spray-cooling based antagonistic SMA actuator (SCASA) was proposed, aiming to address the existing challenges in antagonistic SMA actuators. Theoretical modeling of the SCASA was comprehensively investigated. Experimental findings highlight the superior cooling efficacy of the spray-cooling method, attaining a cooling rate surpassing 100 °C per second for a single SMA spring. Using the spray-cooling based method, the driving frequency of a single SMA spring is approximately twice that of the forced-air cooling method. Experimental results also demonstrate the superior performance of the SCASA using the spray-cooling method, resulting in a reduction of approximately 50% in resistance consumption and an increase of approximately 40% in driving frequency compared to the forced-air method. This work elucidates the promising application prospects of the spray-cooling method in SMA actuators.

Development and Preliminary Evaluation of a Robotic Device for MRI-Guided Needle Breast Biopsy

This study concerns the development and evaluation of a simple and ergonomic robotic system for Magnetic Resonance Imaging (MRI)-guided needle breast biopsy with lateral needle approach. The device comprises two piezoelectrically actuated linear motion stages intended to align a needle supporter with the target for manual needle insertion. The device demonstrated submillimeter accuracy and safe operation within a 3 T clinical MRI scanner. In phantom studies, tumor simulators of varying sizes were successfully targeted in both laboratory and MRI settings.

Improving the kinematic accuracy of a collaborative continuum robot by using flexure-hinges

Within various unstructured industrial environments, there is often the requirement to conduct remote engineering tasks, such as sampling the structure for analysis prior to decommissioning. Most existing tools are simply not dexterous enough to fulfil this task, and thus new technology is required. We describe here a simple, lightweight, and water-resistant collaborative dual-arm continuum robot system which can aid in this task. To improve the kinematic accuracy of the system, a class of flexible hinges have been combined with a conventional continuum robot configuration. The thickness and width of said flexible hinges can be adjusted to adapt to various tasks. Kinematic and stiffness models have further been developed, incorporating the influence of these flexible hinges. A set of experiments have been conducted to validate the proposed model and demonstrate the advantages of the platform. It was found that the kinematic accuracy of the continuum robot can be improved by a factor of around 10 with the aid of said hinges.

Warehouse Management BOT Using Arduino

bstract: Today’s modern world where technical and scientific developments are at a complete innovative intensity, the field of robotics also has experienced an immense bound. Nowadays, in many field robotics and automation is substituted “human touch” to make things easier and better. The critical situations such as aftermath of human and natural disasters, robots can be utilized instead of humans to avoid more casualties. Robotics can also be employed for warehouse management. Human beings pick and choose things up exclusive of thinking about the stages implicated. As a robotic arm or a simple robot system to move or pick up something, someone has to instruct it to execute numerous actions in a correct order for the movement of the robot. This work aims to contribute towards the above mentioned applications using a proposed model to control a warehouse using robot.

Turning machines: a simple algorithmic model for molecular robotics

Molecular robotics is challenging, so it seems best to keep it simple. We consider an abstract molecular robotics model based on simple folding instructions that execute asynchronously. Turning Machines are a simple 1D to 2D folding model, also easily generalisable to 2D to 3D folding. A Turning Machine starts out as a line of connected monomers in the discrete plane, each with an associated turning number. A monomer turns relative to its neighbours, executing a unit-distance translation that drags other monomers along with it, and through collective motion the initial set of monomers eventually folds into a programmed shape. We provide a suite of tools for reasoning about Turning Machines by fully characterising their ability to execute line rotations: executing an almost-full line rotation of 5π/3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$5\\pi /3$$\\end{document} radians is possible, yet a full 2π\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2\\pi$$\\end{document} rotation is impossible. Furthermore, line rotations up to 5π/3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$5\\pi /3$$\\end{document} are executed efficiently, in O(logn)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O(\\log n)$$\\end{document} expected time in our continuous time Markov chain time model. We then show that such line-rotations represent a fundamental primitive in the model, by using them to efficiently and asynchronously fold shapes. In particular, arbitrarily large zig-zag-rastered squares and zig-zag paths are foldable, as are y-monotone shapes albeit with error (bounded by perimeter length). Finally, we give shapes that despite having paths that traverse all their points, are in fact impossible to fold, as well as techniques for folding certain classes of (scaled) shapes without error. Our approach relies on careful geometric-based analyses of the feats possible and impossible by a very simple robotic system, and pushes conceptional hardness towards mathematical analysis and away from molecular implementation.

Development of a Simple Robotic Driver System (SimRoDS) to Test Fuel Economy of Hybrid Electric and Plug-In Hybrid Electric Vehicles Using Fuzzy-PI Control

Over the past decade, new models of hybrid electric vehicles have been released worldwide, and the fuel efficiency of said vehicles has increased by more than 5%. To further improve fuel efficiency, vehicle manufacturers have made efforts to design modules (e.g., engines, motors, transmissions, and batteries) with the highest efficiency possible. To do so, the fuel economy test process, which is conducted primarily using a chassis dynamometer, must produce reliable and accurate results. To accurately analyze the fuel efficiency improvement rate of each module, it is necessary to reduce the test deviation. When the test conducted by human drivers, the test deviation is somewhat large. When the test is conducted by a physical robot driver, the test deviation is improved; however, these robots are expensive and time-consuming to install and take up considerable amount of space in the driver’s seat. To compensate for these shortcomings, we propose a simple, structured robot system that manipulates electrical signals without using mechanical link structures. The controller of this robot driver uses the widely used PI controller. Although PI controllers are simple and perform well, since the dynamics of each test vehicle is different (e.g., acceleration response), the PI controller has a disadvantage in that it cannot determine the optimal PI gain value for each vehicles. In this work, the fuzzy control theorem is applied to overcome this disadvantage. By using fuzzy control to deduce the optimal value of the PI gain, we confirmed that our proposed system is available to conduct tests on vehicles with different dynamics.

Bootstrapped Motion of an Agent on an Adaptive Resource Landscape

We theoretically show that isolated agents that locally and symmetrically consume resources and sense positive resource gradients can generate constant motion via bootstrapped resource gradients in the absence of any externally imposed gradients, and we show a realization of this motion using robots. This self-generated agent motion can be coupled with neighboring agents to act as a spontaneously broken symmetry seed for emergent collective dynamics. We also show that in a sufficiently weak externally imposed gradient, it is possible for an agent to move against an external resource gradient due to the local resource depression on the landscape created by an agent. This counter-intuitive boot-strapped motion against an external gradient is demonstrated with a simple robot system on an light-emitting diode (LED) light-board.

Development of Duplex Eye Contact Framework for Human-Robot Inter Communication

Establishing eye contact is the fundamental key to begin any interaction between human-human and robot-human. Two approaches are available to develop an eye contact mechanism for robot-human interaction, such as simplex and duplex. The two most critical tasks: gaze crossing and gaze awareness, are prerequisite to implementing an active eye contact mechanism in any approach. However, most past robot-human interaction studies implemented a gaze crossing function to develop eye contact in the simplex mode where a robot holds for the human to initiate the communication. However, implementing gaze crossing alone is inadequate to create an active eye contact episode; the gaze awareness function also essential to achieve. This paper aims to develop a mechanism of duplex eye contact for robot-human inter-communication satisfying both functions. This work proposes a conceptual model of a duplex eye contact mechanism considering two cases: human initiative (where the human starts communication with the robot) and robot initiative (where the robot starts the communication with the participant) to achieve a duplex eye contact mechanism. Moreover, a simple robotic system is developed consisting of four software constituents: face detection module, gaze detection and tracking module, gaze awareness module, and robot response and control module to implement the conceptual model of duplex eye contact. Several preliminary experiments are performed to extract necessary cues for designing the duplex eye contact mechanism’s behavioural protocol and present their results to show the usefulness of extracted cues. Moreover, the robotic framework results in a scenario ( e.g., reading the book ) with the proposed duplex eye contact mechanism are presented. The results show that the proposed scheme achieved 92% and 86% accuracy for human initiative case and robot initiative case, respectively in making eye contact.

Gaussian Variational State Estimation for Nonlinear State-Space Models

In this paper, the problem of state estimation, in the context of both filtering and smoothing, for nonlinear state-space models is considered. Due to the nonlinear nature of the models, the state estimation problem is generally intractable as it involves integrals of general nonlinear functions and the filtered and smoothed state distributions lack closed-form solutions. As such, it is common to approximate the state estimation problem. In this paper, we develop an assumed Gaussian solution based on variational inference, which offers the key advantage of a flexible, but principled, mechanism for approximating the required distributions. Our main contribution lies in a new formulation of the state estimation problem as an optimisation problem, which can then be solved using standard optimisation routines that employ exact first- and second-order derivatives. The resulting state estimation approach involves a minimal number of assumptions and applies directly to nonlinear systems with both Gaussian and non-Gaussian probabilistic models. The performance of our approach is demonstrated on several examples; a challenging scalar system, a model of a simple robotic system, and a target tracking problem using a von Mises-Fisher distribution and outperforms alternative assumed Gaussian approaches to state estimation.

A Remote-Controlled Robotic System with Safety Protection Strategy Based on Force-Sensing and Bending Feedback for Transcatheter Arterial Chemoembolization.

Transcatheter arterial chemoembolization (TACE) is the common choice of non-open surgery for hepatocellular carcinoma (HCC) now. In this study, a simple TACE robotic system of 4-degree-of-freedom is proposed to get higher accuracy and stability of the surgery operation and reduce X-ray exposure time of the surgeons. The master–slave control strategy is adopted in the robotic system and a customized sigmoid function is designed to optimize the joystick control of the master–slave robotic control system. A force-sensing module is developed to sense the resistance of the guide wire in linear delivery motion and an auxiliary bending feedback method based on constraint pipe with a film sensor is proposed. With two force-sensing methods, the safety strategy of robotic motion with 9 different motion constraint coefficients is given and a human–computer interface is developed. The TACE robot would monitor the value of the force sensor and the analog voltage of the film sensor to adopt the corresponding motion constraint coefficient in every 10 ms. Vascular model experiments were performed to validate the robotic system, and the results showed that the safety strategy could improve the reliability of the operation with immediate speed constraint and avoid potential aggressive delivery.

Drive Through Robotics: Robotic Automation for Last Mile Distribution of Food and Essentials During Pandemics.

The COVID-19 pandemic unraveled the weak points in the global supply chain for goods. Specifically, people all over the world, including those in the most advanced nations have had to go without medical supplies and personal protective equipment. Scarcity of essentials increases anxiety and uncertainty exacerbating unproductive behaviors like hoarding and price gouging. Left to market forces, such unfair practices are likely to aggravate hardships and increase the loss of lives. Thus, there is a critical need to ensure safe distribution of food and essential supplies to all citizens to sustain them through challenging times. To this end, we propose a simple, affordable and contact-less robotic system for preparing and dispensing food and survival-kits at community scale. The system has provisions to prevent hoarding and price gouging. Design, simulation, and, validation of the system has been completed to ensure readiness for real world implementation. This project is part of an open-source program and detailed designs are available upon request to entities interested in using it to serve their communities.

Automated fluid delivery from multiwell plates to microfluidic devices for high-throughput experiments and microscopy

High-throughput biological and chemical experiments typically use either multiwell plates or microfluidic devices to analyze numerous independent samples in a compact format. Multiwell plates are convenient for screening chemical libraries in static fluid environments, whereas microfluidic devices offer immense flexibility in flow control and dynamics. Interfacing these platforms in a simple and automated way would introduce new high-throughput experimental capabilities, such as compound screens with precise exposure timing. Whereas current approaches to integrate microfluidic devices with multiwell plates remain expensive or technically complicated, we present here a simple open-source robotic system that delivers liquids sequentially through a single connected inlet. We first characterized reliability and performance by automatically delivering 96 dye solutions to a microfluidic device. Next, we measured odor dose-response curves of in vivo neural activity from two sensory neuron types in dozens of living C. elegans in a single experiment. We then identified chemicals that suppressed optogenetically-evoked neural activity, demonstrating a functional screening platform for neural modulation in whole organisms. Lastly, we automated an 85-minute, ten-step cell staining protocol. Together, these examples show that our system can automate various protocols and accelerate experiments by economically bridging two common elements of high-throughput systems: multiwell plates and microfluidics.

Feedback Error Learning Controller for Functional Electrical Stimulation Assistance in a Hybrid Robotic System for Reaching Rehabilitation.

Hybrid robotic systems represent a novel research field, where functional electrical stimulation (FES) is combined with a robotic device for rehabilitation of motor impairment. Under this approach, the design of robust FES controllers still remains an open challenge. In this work, we aimed at developing a learning FES controller to assist in the performance of reaching movements in a simple hybrid robotic system setting. We implemented a Feedback Error Learning (FEL) control strategy consisting of a feedback PID controller and a feedforward controller based on a neural network. A passive exoskeleton complemented the FES controller by compensating the effects of gravity. We carried out experiments with healthy subjects to validate the performance of the system. Results show that the FEL control strategy is able to adjust the FES intensity to track the desired trajectory accurately without the need of a previous mathematical model.

Design and Calibration of a Soft Multiple Degree of Freedom Motion Sensor System Based On Dielectric Elastomers

Abstract Soft robots use active deformable structures to provide highly capable yet simple and robust robotic systems. Motion sensors for soft robots must, therefore, be able to provide joint position sensing on deformable, multiple degrees of freedom (DOFs) joints often found in soft robot architectures and whose kinematics are not accurately described by closed-form mathematical models. This article proposes a method for designing dielectric elastomer sensor systems for such soft robots. The method is presented as a case study of a soft sensor system for an existing robotic manipulator designed for magnetic resonance image-guided surgery to the prostate. A calibration method based on support vector regression (SVR) is proposed to calibrate the coupled, multi-DOFs sensor system without a model. A prototype sensor system is built and is shown to reach a precision of 0.3 mm root mean square/1.2 mm maximum when calibrated with SVR. These results show sufficient precision for many applications and suggest th...

Towards an artificial vision-robotic system for tomato identification

In the present paper we developed a simple and affordable vision-based robotic system for the identification of the Euclidean position of red spheres that emulate ripe tomatoes. This is done by using a RGB-D sensor in a fixed position, together with a 5 DOF manipulator. To detect the tomato the sensor considers it as a red blob and then it calculates its center using a point cloud map. The position of the red blob is mapped to the manipulator reference frame using the homogeneous transformation matrix from the camera to the manipulator. The position of the sphere is sent through a micro-controller to drive the manipulator, with the purpose of reaching the sphere’s position. Experimental results of the vision-based robotic system are provided, and the system accuracy obtained in localizing and touching the interest object demonstrate to be highly effective, reaching an accuracy of 10/10 in identification and touching the object in ideal environment.

Engineering central pattern generated behaviors for the deployment of robotic systems

In order to face with various contexts and situations, autonomous robots should be endowed with many different sensors and behaviors. These requirements pose new challenges such as the coordination of multiple parallel activities and the efficient use of the limited sensorial and cognitive resources. These challenges are often tackled by relying on a priori and well defined coordination schema among behaviors, and on fixed periodic or ad hoc monitoring strategies. Our working hypothesis is that adaptive control strategies, inspired by natural cyclic processes, can be used to cope with these problems. However, the development of these flexible strategies may result hard to be modeled and implemented. Recently, the possibility of abstracting an implementation view into an architectural design is getting more achievable. Hence, in this paper, we propose a modeling framework that allows developers to model simple behavior-based robotic systems enhanced by the use of Central Pattern Generators (CPGs) for modulating the sensor-motor loops. Different from other approaches, the use of CPGs, here, is to efficiently exploit the limited sensorial and cognitive resources, and to coordinate the multiple activities the robot is endowed with, by balancing sensors elaboration and action execution. The framework can use these models to generate robotic control executable code for analysis purposes. In this paper, we focus on parallel behaviors managing analysis.

Robotics-assisted mass spectrometry assay platform enabled by open-source electronics

Mass spectrometry (MS) is an important analytical technique with numerous applications in clinical analysis, biochemistry, environmental analysis, geology and physics. Its success builds on the ability of MS to determine molecular weights of analytes, and elucidate their structures. However, sample handling prior to MS requires a lot of attention and labor. In this work we were aiming to automate processing samples for MS so that analyses could be conducted without much supervision of experienced analysts. The goal of this study was to develop a robotics and information technology-oriented platform that could control the whole analysis process including sample delivery, reaction-based assay, data acquisition, and interaction with the analyst. The proposed platform incorporates a robotic arm for handling sample vials delivered to the laboratory, and several auxiliary devices which facilitate and secure the analysis process. They include: multi-relay board, infrared sensors, photo-interrupters, gyroscopes, force sensors, fingerprint scanner, barcode scanner, touch screen panel, and internet interface. The control of all the building blocks is achieved through implementation of open-source electronics (Arduino), and enabled by custom-written programs in C language. The advantages of the proposed system include: low cost, simplicity, small size, as well as facile automation of sample delivery and processing without the intervention of the analyst. It is envisaged that this simple robotic system may be the forerunner of automated laboratories dedicated to mass spectrometric analysis of biological samples.

윤곽선의 선분 근사화를 활용한 양팔 화가 로봇의 개발

This paper introduces a dual-arm robot painter system which is capable of sketching a camera-captured image with short line segments. To express various curved edges in the image by combining line segments, we first apply edge detection algorithm to the entire image, split the edged image into small boxed pieces, and then apply Hough Transformation to each piece so that the edges inside the piece can be approximated with short line segments. To draw the picture within a reasonable time, we designed a simple dual-arm robot system and controlled both arms concurrently according to linear interpolation algorithm. From the experiments, we could verify that simple linear motions can describe various images effectively with a unique brush style.

The Use of Macroarray as a Simple Tool to Follow the Metabolic Profile of <i>Lactobacillus plantarum</i> during Fermentation

This study focused on defining the differences in L. plantarum gene expression levels in different media and in different growth phases using an easy and cost-efficient monitoring of gene expression. A macroarray based on a group of selected L. plantarum genes, 178 genes belonging to 18 main groups, printed onto a nitrocellulose filter was designed in this work. Using the macrofilters designed, the expression of a selected set of L. plantarum genes was assayed in synthetic MRS medium and in extracted carrot juice. To compare the potential differences of starter gene expression in hygienic and contaminated cultivation media, the L. plantarum strain was cultivated in both sterile and contaminated (yeast and Escherichia coli) MRS and carrot juice. The number of genes found to be regulated as a function of growth was clearly higher in MRS-based growth medium than in carrot juice, In carrot juice, expression of the gene encoding malolactic enzyme (MLE), which makes L. plantarum an advantageous microbe in e.g. wine making, was found to be upregulated in logarithmic phase of growth. The current study demonstrated that macroarrays printed on nitrocellulose filters with simple robotic systems can be analyzed by standard laboratory equipment and methods usually available in molecular laboratories. Using this technology, rapid and cost-efficient analysis of genome function of L. plantarum can be carried out e.g. in developing regions, where lactic acid fermentation of food and feed matrices is a common practice.

End-Effector Position Analysis Using Forward Kinematics For 5 Dof Pravak Robot Arm

Automatic control of the robotic manipulator involves study of kinematics and dynamics as a major issue. This paper involves the kinematic analysis of a Pravak Robot arm which is used for doing successful robotic manipulation task in its workspace. The Pravak Robot Arm is a 5-DOF robot having all the joints revolute. The kinematics problem is defined as the transformation from the Cartesian space to the joint space and vice versa. In this study the Denavit- Hartenberg (D-H) model is used to model robot links and joints. Pravak Robot Arm is a simple and safe robotic system designed for laboratory training and research applications. This robot allows to gain theoretical and practical experience in robotics, automation and control systems. The MATLAB R2007 is used to analyse end effectors position for a set of joint parameter.