scholarly journals Hardware Methods for Onboard Control of Fluidically Actuated Soft Robots

2021 ◽  
Vol 8 ◽  
Author(s):  
Kevin McDonald ◽  
Tommaso Ranzani
Keyword(s):  
Degrees Of Freedom ◽  
Review Paper ◽  
State Of The Art ◽  
Human Interaction ◽  
Power Delivery ◽  
Soft Robots ◽  
Integrate Control ◽  
Working Together ◽  
Multiple Actuators ◽  
Reaction Speed

Soft robots provide significant advantages over their rigid counterparts. These compliant, dexterous devices can navigate delicate environments with ease without damage to themselves or their surroundings. With many degrees of freedom, a single soft robotic actuator can achieve configurations that would be very challenging to obtain when using a rigid linkage. Because of these qualities, soft robots are well suited for human interaction. While there are many types of soft robot actuation, the most common type is fluidic actuation, where a pressurized fluid is used to inflate the device, causing bending or some other deformation. This affords advantages with regards to size, ease of manufacturing, and power delivery, but can pose issues when it comes to controlling the robot. Any device capable of complex tasks such as navigation requires multiple actuators working together. Traditionally, these have each required their own mechanism outside of the robot to control the pressure within. Beyond the limitations on autonomy that such a benchtop controller induces, the tether of tubing connecting the robot to its controller can increase stiffness, reduce reaction speed, and hinder miniaturization. Recently, a variety of techniques have been used to integrate control hardware into soft fluidic robots. These methods are varied and draw from disciplines including microfluidics, digital logic, and material science. In this review paper, we discuss the state of the art of onboard control hardware for soft fluidic robots with an emphasis on novel valve designs, including an overview of the prevailing techniques, how they differ, and how they compare to each other. We also define metrics to guide our comparison and discussion. Since the uses for soft robots can be so varied, the control system for one robot may very likely be inappropriate for use in another. We therefore wish to give an appreciation for the breadth of options available to soft roboticists today.

scholarly journals Soft Robotics: Biological Inspiration, State of the Art, and Future Research

2008 ◽  
Vol 5 (3) ◽  
pp. 99-117 ◽  
Author(s):  
Deepak Trivedi ◽  
Christopher D. Rahn ◽  
William M. Kier ◽  
Ian D. Walker
Keyword(s):  
Degrees Of Freedom ◽  
State Of The Art ◽  
Future Research ◽  
Robot Design ◽  
The Novel ◽  
Soft Robots ◽  
Biological Inspiration ◽  
End Effectors ◽  
And Control ◽  
Complex Movement

Traditional robots have rigid underlying structures that limit their ability to interact with their environment. For example, conventional robot manipulators have rigid links and can manipulate objects using only their specialised end effectors. These robots often encounter difficulties operating in unstructured and highly congested environments. A variety of animals and plants exhibit complex movement with soft structures devoid of rigid components. Muscular hydrostats (e.g. octopus arms and elephant trunks) are almost entirely composed of muscle and connective tissue and plant cells can change shape when pressurised by osmosis. Researchers have been inspired by biology to design and build soft robots. With a soft structure and redundant degrees of freedom, these robots can be used for delicate tasks in cluttered and/or unstructured environments. This paper discusses the novel capabilities of soft robots, describes examples from nature that provide biological inspiration, surveys the state of the art and outlines existing challenges in soft robot design, modelling, fabrication and control.

scholarly journals Task space adaptation via the learning of gait controllers of magnetic soft millirobots

2021 ◽  
pp. 027836492110218
Author(s):  
Sinan O. Demir ◽  
Utku Culha ◽  
Alp C. Karacakol ◽  
Abdon Pena-Francesch ◽  
Sebastian Trimpe ◽  
...  
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Bayesian Optimization ◽  
Small Scale ◽  
Soft Robots ◽  
Modeling And Control ◽  
Walking Gait ◽  
Physical Experiments ◽  
Efficient Learning ◽  
Task Environments

Untethered small-scale soft robots have promising applications in minimally invasive surgery, targeted drug delivery, and bioengineering applications as they can directly and non-invasively access confined and hard-to-reach spaces in the human body. For such potential biomedical applications, the adaptivity of the robot control is essential to ensure the continuity of the operations, as task environment conditions show dynamic variations that can alter the robot’s motion and task performance. The applicability of the conventional modeling and control methods is further limited for soft robots at the small-scale owing to their kinematics with virtually infinite degrees of freedom, inherent stochastic variability during fabrication, and changing dynamics during real-world interactions. To address the controller adaptation challenge to dynamically changing task environments, we propose using a probabilistic learning approach for a millimeter-scale magnetic walking soft robot using Bayesian optimization (BO) and Gaussian processes (GPs). Our approach provides a data-efficient learning scheme by finding the gait controller parameters while optimizing the stride length of the walking soft millirobot using a small number of physical experiments. To demonstrate the controller adaptation, we test the walking gait of the robot in task environments with different surface adhesion and roughness, and medium viscosity, which aims to represent the possible conditions for future robotic tasks inside the human body. We further utilize the transfer of the learned GP parameters among different task spaces and robots and compare their efficacy on the improvement of data-efficient controller learning.

scholarly journals The Understanding of Deep Learning: A Comprehensive Review

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Ranjan Kumar Mishra ◽  
G. Y. Sandesh Reddy ◽  
Himanshu Pathak
Keyword(s):  
Deep Learning ◽  
Deep Neural Network ◽  
Computational Models ◽  
Review Paper ◽  
State Of The Art ◽  
Visual Object ◽  
Visual Object Recognition ◽  
Levels Of Abstraction ◽  
Comprehensive Review ◽  
Computer Based

Deep learning is a computer-based modeling approach, which is made up of many processing layers that are used to understand the representation of data with several levels of abstraction. This review paper presents the state of the art in deep learning to highlight the major challenges and contributions in computer vision. This work mainly gives an overview of the current understanding of deep learning and their approaches in solving traditional artificial intelligence problems. These computational models enhanced its application in object detection, visual object recognition, speech recognition, face recognition, vision for driverless cars, virtual assistants, and many other fields such as genomics and drug discovery. Finally, this paper also showcases the current developments and challenges in training deep neural network.

scholarly journals Preface to the April 2018 Issue including selected works from CIbSE 2017 and LACLO 2016

2018 ◽  
Vol 21 (1) ◽  
Author(s):  
Héctor Cancela ◽  
Isabel Brito ◽  
Luca Cernuzzi ◽  
Marcela Genero ◽  
Jesús García Molina ◽  
...  
Keyword(s):  
Costa Rica ◽  
Software Engineering ◽  
Latin American ◽  
Buenos Aires ◽  
Review Paper ◽  
State Of The Art ◽  
Contextual Information ◽  
Learning Objects ◽  
The State ◽  
San Jose

This issue of the CLEIej consists of three main parts: i) a review paper on the state of the art of how contextual information extracted from a user task can help to improve searches for contents relevant to this task; ii) extended and revised versions of Selected Papers (which correspond to the second and third best paper from each track) presented at the XX Ibero-American Conference on Software Engineering (CIbSE 2017), which took place in Buenos Aires, Argentina, in May 2017; and, iii) extended and revised versions of selected papers from LACLO 2016, the XI Latin American Conference on Learning Objects and Technology, which took place in San José, Costa Rica, in October 2016.

scholarly journals Tunnel Squeezing Deformation Control and the Use of Yielding Elements in Shotcrete Linings: A Review

Materials ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 391
Author(s):  
Xiaomeng Zheng ◽  
Kui Wu ◽  
Zhushan Shao ◽  
Bo Yuan ◽  
Nannan Zhao
Keyword(s):  
High Resistance ◽  
Review Paper ◽  
State Of The Art ◽  
Squeezing Ground ◽  
Deformation Control ◽  
Development History ◽  
Ground Conditions ◽  
Supporting Effect ◽  
Mechanical Performances ◽  
Shotcrete Lining

Shotcrete lining shows high resistance but extremely low deformability. The utilization of yielding elements in shotcrete lining, which leads to the so-called ductile lining, provides a good solution to cope with tunnel squeezing deformations. Although ductile lining exhibits great advantages regarding tunnel squeezing deformation control, little information has been comprehensively and systematically available for its mechanism and design. This is a review paper for the purpose of summarizing the development history and discussing the state of the art of ductile lining. It begins by providing a brief introduction of ductile lining and an explanation of the importance of studying this issue. A following summary of supporting mechanism and benefits of ductile lining used in tunnels excavated in squeezing ground conditions is provided. Then, it summarizes the four main types of yielding elements applied in shotcrete lining and introduces their basic structures and mechanical performances. The influences of parameters of yielding elements on the supporting effect are discussed and the design methods for ductile lining are reviewed as well. Furthermore, recommendations for further research in ductile lining are proposed. Finally, a brief summary is presented.

scholarly journals Review of single clustering methods

2019 ◽  
Vol 8 (3) ◽  
pp. 221
Author(s):  
Nurshazwani Muhamad Mahfuz ◽  
Marina Yusoff ◽  
Zakiah Ahmad
Keyword(s):  
Data Analytics ◽  
Review Paper ◽  
State Of The Art ◽  
Learning Method ◽  
Clustering Methods ◽  
Optimal Result ◽  
Clustering Method ◽  
Noise Data ◽  
Research Findings ◽  
Real World Problems

<div style="’text-align: justify;">Clustering provides a prime important role as an unsupervised learning method in data analytics to assist many real-world problems such as image segmentation, object recognition or information retrieval. It is often an issue of difficulty for traditional clustering technique due to non-optimal result exist because of the presence of outliers and noise data.  This review paper provides a review of single clustering methods that were applied in various domains.  The aim is to see the potential suitable applications and aspect of improvement of the methods. Three categories of single clustering methods were suggested, and it would be beneficial to the researcher to see the clustering aspects as well as to determine the requirement for clustering method for an employment based on the state of the art of the previous research findings.</div>

scholarly journals High-Dimensional Pixel Entanglement: Efficient Generation and Certification

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 376
Author(s):  
Natalia Herrera Valencia ◽  
Vatshal Srivastav ◽  
Matej Pivoluska ◽  
Marcus Huber ◽  
Nicolai Friis ◽  
...  
Keyword(s):  
Carrying Capacity ◽  
Communication Systems ◽  
Degrees Of Freedom ◽  
State Of The Art ◽  
Quality Measurement ◽  
High Dimensional ◽  
Single Photons ◽  
Spatial Mode ◽  
Classical Communication ◽  
Entanglement Of Formation

Photons offer the potential to carry large amounts of information in their spectral, spatial, and polarisation degrees of freedom. While state-of-the-art classical communication systems routinely aim to maximize this information-carrying capacity via wavelength and spatial-mode division multiplexing, quantum systems based on multi-mode entanglement usually suffer from low state quality, long measurement times, and limited encoding capacity. At the same time, entanglement certification methods often rely on assumptions that compromise security. Here we show the certification of photonic high-dimensional entanglement in the transverse position-momentum degree-of-freedom with a record quality, measurement speed, and entanglement dimensionality, without making any assumptions about the state or channels. Using a tailored macro-pixel basis, precise spatial-mode measurements, and a modified entanglement witness, we demonstrate state fidelities of up to 94.4% in a 19-dimensional state-space, entanglement in up to 55 local dimensions, and an entanglement-of-formation of up to 4 ebits. Furthermore, our measurement times show an improvement of more than two orders of magnitude over previous state-of-the-art demonstrations. Our results pave the way for noise-robust quantum networks that saturate the information-carrying capacity of single photons.

scholarly journals A Review of PZT Patches Applications in Submerged Systems

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2251 ◽  
Author(s):  
Alexandre Presas ◽  
Yongyao Luo ◽  
Zhengwei Wang ◽  
David Valentin ◽  
Mònica Egusquiza
Keyword(s):  
Energy Harvesting ◽  
System Dynamics ◽  
Vibration Control ◽  
Structural Properties ◽  
Environmental Conditions ◽  
Review Paper ◽  
State Of The Art ◽  
Atomic Force ◽  
Working Medium ◽  
Mechanical And Structural Properties

Submerged systems are found in many engineering, biological, and medicinal applications. For such systems, due to the particular environmental conditions and working medium, the research on the mechanical and structural properties at every scale (from macroscopic to nanoscopic), and the control of the system dynamics and induced effects become very difficult tasks. For such purposes in submerged systems, piezoelectric patches (PZTp), which are light, small and economic, have been proved to be a very good solution. PZTp have been recently used as sensors/actuators for applications such as modal analysis, active sound and vibration control, energy harvesting and atomic force microscopes in submerged systems. As a consequence, in these applications, newly developed transducers based on PZTp have become the most used ones, which has improved the state of the art and methods used in these fields. This review paper carefully analyzes and summarizes these applications particularized to submerged structures and shows the most relevant results and findings, which have been obtained thanks to the use of PZTp.

scholarly journals Hydrothermal Carbonization of Organic Waste and Biomass: A Review on Process, Reactor, and Plant Modeling

2020 ◽  
Author(s):  
Giulia Ischia ◽  
Luca Fiori
Keyword(s):  
Organic Waste ◽  
Review Paper ◽  
Recent Literature ◽  
State Of The Art ◽  
Hydrothermal Carbonization ◽  
Residual Biomass ◽  
Current State ◽  
Potential Applications ◽  
Intrinsic Complexity ◽  
Context Models

Abstract Hydrothermal carbonization (HTC) is an emerging path to give a new life to organic waste and residual biomass. Fulfilling the principles of the circular economy, through HTC “unpleasant” organics can be transformed into useful materials and possibly energy carriers. The potential applications of HTC are tremendous and the recent literature is full of investigations. In this context, models capable to predict, simulate and optimize the HTC process, reactors, and plants are engineering tools that can significantly shift HTC research towards innovation by boosting the development of novel enterprises based on HTC technology. This review paper addresses such key-issue: where do we stand regarding the development of these tools? The literature presents many and simplified models to describe the reaction kinetics, some dealing with the process simulation, while few focused on the heart of an HTC system, the reactor. Statistical investigations and some life cycle assessment analyses also appear in the current state of the art. This work examines and analyzes these predicting tools, highlighting their potentialities and limits. Overall, the current models suffer from many aspects, from the lack of data to the intrinsic complexity of HTC reactions and HTC systems. Therefore, the emphasis is given to what is still necessary to make the HTC process duly simulated and therefore implementable on an industrial scale with sufficient predictive margins. Graphic Abstract

scholarly journals A critical review of the data pipeline: how wastewater system operation flows from data to intelligence

2020 ◽  
Vol 82 (12) ◽  
pp. 2613-2634
Author(s):  
Jean-David Therrien ◽  
Niels Nicolaï ◽  
Peter A. Vanrolleghem
Keyword(s):  
Current Practice ◽  
Review Paper ◽  
State Of The Art ◽  
Data Driven ◽  
Sensor Data ◽  
Measurement Technology ◽  
Efficient Operation ◽  
Smart Water ◽  
Data Pipeline ◽  
Systems Models

Abstract Faced with an unprecedented amount of data coming from evermore ubiquitous sensors, the wastewater treatment community has been hard at work to develop new monitoring systems, models and controllers to bridge the gap between current practice and data-driven, smart water systems. For additional sensor data and models to have an appreciable impact, however, they must be relevant enough to be looked at by busy water professionals; be clear enough to be understood; be reliable enough to be believed and be convincing enough to be acted upon. Failure to attain any one of those aspects can be a fatal blow to the adoption of even the most promising new measurement technology. This review paper examines the state-of-the-art in the transformation of raw data into actionable insight, specifically for water resource recovery facility (WRRF) operation. Sources of difficulties found along the way are pinpointed, while also exploring possible paths towards improving the value of collected data for all stakeholders, i.e., all personnel that have a stake in the good and efficient operation of a WRRF.

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