114 research outputs found
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Shape memory meta-laminar jamming actuators fabricated by 4D printing
Laminar jamming (LJ) technology is a hot topic because it allows for the transition from conventionally quick, precise, and high-force rigid robots to flexible, agile, and secure soft robots. This article introduces a novel conceptual design of meta-laminar jamming (MLJ) actuators with a polyurethane shape memory polymer (SMP)-based meta-structure fabricated by 4D printing (4DP). The sustainable MLJ actuators behave as soft/hard robots via hot and cold programming accompanied by negative air pressure. The advantage of MLJ actuators over conventional LJ actuators is that a continuous negative air pressure is not required to stimulate the actuator. SMP meta-structures with circle, rectangle, diamond, and auxetic shapes are 4D printed. Mechanical properties of the structures are evaluated through three-point bending and compression tests. Shape memory effects (SMEs) and shape recovery of meta-structures and MLJ actuators are investigated via hot air programming. MLJ actuators with auxetic meta-structure cores show a better performance in terms of contraction and bending with 100% shape recovery after stimulation. The sustainable MLJ actuators have the capabilities of shape recovery and shape locking with zero input power while holding 200 g weight. The actuator can easily lift and hold objects of varying weights and shapes without requiring any power input. This actuator has demonstrated its versatility in potential applications, such as functioning as an end-effector and a gripper device
Design of a robotic flexible actuator based on layer jamming
This research paper provides an insight into one of the most promising fields of robotics, which brings together two main elements: the traditional or rigid robotics and the soft robotics. A branch of soft-rigid robots can perform and modulate soft and rigid configurations by means of an approach called jamming. Here we explore how to use layer jamming, namely a set of layers within a flexible membrane, in order to design soft robotics.
The paper introduces a quick overview of the history of soft robotics, then it presents the design of a functional prototype of soft-rigid robotic arm with the results of preliminary trials and discussion of future advances where we show the capability of the system in order to lift up possible loads
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Soft pneumatic actuators: a review of design, fabrication, modeling, sensing, control and applications
Soft robotics is a rapidly evolving field where robots are fabricated using highly deformable materials and usually follow a bioinspired design. Their high dexterity and safety make them ideal for applications such as gripping, locomotion, and biomedical devices, where the environment is highly dynamic and sensitive to physical interaction. Pneumatic actuation remains the dominant technology in soft robotics due to its low cost and mass, fast response time, and easy implementation. Given the significant number of publications in soft robotics over recent years, newcomers and even established researchers may have difficulty assessing the state of the art. To address this issue, this article summarizes the development of soft pneumatic actuators and robots up until the date of publication. The scope of this article includes the design, modeling, fabrication, actuation, characterization, sensing, control, and applications of soft robotic devices. In addition to a historical overview, there is a special emphasis on recent advances such as novel designs, differential simulators, analytical and numerical modeling methods, topology optimization, data-driven modeling and control methods, hardware control boards, and nonlinear estimation and control techniques. Finally, the capabilities and limitations of soft pneumatic actuators and robots are discussed and directions for future research are identified
Deep reinforcement learning for soft, flexible robots : brief review with impending challenges
The increasing trend of studying the innate softness of robotic structures and amalgamating it with the benefits of the extensive developments in the field of embodied intelligence has led to the sprouting of a relatively new yet rewarding sphere of technology in intelligent soft robotics. The fusion of deep reinforcement algorithms with soft bio-inspired structures positively directs to a fruitful prospect of designing completely self-sufficient agents that are capable of learning from observations collected from their environment. For soft robotic structures possessing countless degrees of freedom, it is at times not convenient to formulate mathematical models necessary for training a deep reinforcement learning (DRL) agent. Deploying current imitation learning algorithms on soft robotic systems has provided competent results. This review article posits an overview of various such algorithms along with instances of being applied to real-world scenarios, yielding frontier results. Brief descriptions highlight the various pristine branches of DRL research in soft robotics
A review of infrared thermography applications for ice detection and mitigation
Ice accretion on various onshore and offshore infrastructures imparts hazardous effects sometimes beyond repair,
which may be life-threatening. Therefore, it has become necessary to look for ways to detect and mitigate ice.
Some ice mitigation techniques have been tested or in use in aviation and railway sectors, however, their
applicability to other sectors/systems is still in the research phase. To make such systems autonomous, ice
protection systems need to be accompanied by reliable ice detection systems, which include electronic,
mechatronics, mechanical, and optical techniques. Comparing the benefits and limitations of all available
methodologies, Infrared Thermography (IRT) appears to be one of the useful, non-destructive, and emerging
techniques as it offers wide area monitoring instead of just point-based ice monitoring. This paper reviews the
applications of IRT in the field of icing on various subject areas to provide valuable insights into the existing
development of an intelligent and autonomous ice mitigation system for general applications
Exploring the effects of robotic design on learning and neural control
The ongoing deep learning revolution has allowed computers to outclass humans
in various games and perceive features imperceptible to humans during
classification tasks. Current machine learning techniques have clearly
distinguished themselves in specialized tasks. However, we have yet to see
robots capable of performing multiple tasks at an expert level. Most work in
this field is focused on the development of more sophisticated learning
algorithms for a robot's controller given a largely static and presupposed
robotic design. By focusing on the development of robotic bodies, rather than
neural controllers, I have discovered that robots can be designed such that
they overcome many of the current pitfalls encountered by neural controllers in
multitask settings. Through this discovery, I also present novel metrics to
explicitly measure the learning ability of a robotic design and its resistance
to common problems such as catastrophic interference.
Traditionally, the physical robot design requires human engineers to plan
every aspect of the system, which is expensive and often relies on human
intuition. In contrast, within the field of evolutionary robotics, evolutionary
algorithms are used to automatically create optimized designs, however, such
designs are often still limited in their ability to perform in a multitask
setting. The metrics created and presented here give a novel path to automated
design that allow evolved robots to synergize with their controller to improve
the computational efficiency of their learning while overcoming catastrophic
interference.
Overall, this dissertation intimates the ability to automatically design
robots that are more general purpose than current robots and that can perform
various tasks while requiring less computation.Comment: arXiv admin note: text overlap with arXiv:2008.0639
Recent Progress in Some Aircraft Technologies
The book describes the recent progress in some engine technologies and active flow control and morphing technologies and in topics related to aeroacoustics and aircraft controllers. Both the researchers and students should find the material useful in their work
Aeronautical Engineering: A continuing bibliography with indexes, supplement 185
This bibliography lists 462 reports, articles and other documents introduced into the NASA scientific and technical information system in February 1985. Aerodynamics, aeronautical engineering, aircraft design, aircraft stability and control, geophysics, social sciences, and space sciences are some of the areas covered
On Increasing the Automation Level of Heavy-Duty Hydraulic Manipulators with Condition Monitoring of the Hydraulic System and Energy-Optimised Redundancy Resolution
Hydraulic manipulators on mobile machines are predominantly used for excavation and lifting applications at construction sites and for heavy-duty material handling in the forest industry due to their superior power-density and rugged nature. These manipulators are conventionally open-loop controlled by human operators who are sufficiently skilled to operate the machines. However, in the footsteps of pioneering original equipment manufacturers (OEMs) and to keep up with the intensifying demand for innovation, more and more mobile machine OEMs have a major interest in significantly increasing the automation level of their hydraulic manipulators and improving the operation of manipulators. In this thesis, robotic software-based functionalities in the form of modelbased condition monitoring and energy-optimal redundancy resolution which facilitate increased automation level of hydraulic manipulators are proposed.A condition monitoring system generally consists of software modules and sensors which co-operate harmonically and monitor the hydraulic system’s health in real-time based on an indirect measure of this system’s health. The premise is that when this condition monitoring system recognises that the system’s health has deteriorated past a given threshold (in other words, when a minor fault is detected, such as a slowly increasing internal leakage of the hydraulic cylinder), the condition monitoring module issues an alarm to warn the system operator of the malfunction, and the module could ideally diagnose the fault cause. In addition, when faced with severe faults, such as an external leakage or an abruptly increasing internal leakage in the hydraulic system, an alarm from the condition monitoring system ensures that the machine is quickly halted to prevent any further damage to the machine or its surroundings.The basic requirement in the design of such a condition monitoring system is to make sure that this system is robust and fault-sensitive. These properties are difficult to achieve in complex mobile hydraulic systems on hydraulic manipulators due to the modelling uncertainties affecting these systems. The modelling uncertainties affecting mobile hydraulic systems are specific compared with many other types of systems and are large because of the hydraulic system complexities, nonlinearities, discontinuities and inherently time-varying parameters. A feasible solution to this modelling uncertainty problem would be to either attenuate the effect of modelling errors on the performance of model-based condition monitoring or to develop improved non-model-based methods with increased fault-sensitivity. In this research work, the former model-based approach is taken. Adaptation of the model residual thresholds based on system operating points and reliable, load-independent system models are proposed as integral parts of the condition monitoring solution to the modelling uncertainty problem. These proposed solutions make the realisation of condition monitoring solutions more difficult on heavy-duty hydraulic manipulators compared with fixed-load manipulators, for example. These solutions are covered in detail in a subset of the research publications appended to this thesis.There is wide-spread interest from hydraulic manipulator OEMs in increasing the automation level of their hydraulic manipulators. Most often, this interest is related to semi-automation of repetitive work cycles to improve work productivity and operator workload circumstances. This robotic semi-automated approach involves resolving the kinematic redundancy of hydraulic manipulators to obtain motion references for the joint controller to enable desirable closed-loop controlled motions. Because conventional redundancy resolutions are usually sub-optimal at the hydraulic system level, a hydraulic energy-optimised, global redundancy resolution is proposed in this thesis for the first time. Kinematic redundancy is resolved energy optimally from the standpoint of the hydraulic system along a prescribed path for a typical 3-degrees-of-freedom (3-DOF) and 4-DOF hydraulic manipulator. Joint motions are also constrained based on the actuators’ position, velocity and acceleration bounds in hydraulic manipulators in the proposed solution. This kinematic redundancy resolution topic is discussed in the last two research papers. Overall, both designed manipulator features, condition monitoring and energy-optimised redundancy resolution, are believed to be essential for increasing the automation of hydraulic manipulators
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