10,953 research outputs found
Geometry-based Direct Simulation for Multi-Material Soft Robots
Robots fabricated by soft materials can provide higher flexibility and thus better safety while interacting with natural objects with low stiffness such as food and human beings. However, as many more degrees of freedom are introduced, the motion simulation of a soft robot becomes cumbersome, especially when large deformations are presented. Moreover, when the actuation is defined by geometry variation, it is not easy to obtain the exact loads and material properties to be used in the conventional methods of deformation simulation. In this paper, we present a direct approach to take the geometric actuation as input and compute the deformed shape of soft robots by numerical optimization using a geometry-based algorithm. By a simple calibration, the properties of multiple materials can be modeled geometrically in the framework. Numerical and experimental tests have been conducted to demonstrate the performance of our approach on both cable-driven and pneumatic actuators in soft robotics
3D Printed Soft Robotic Hand
Soft robotics is an emerging industry, largely dominated by companies which hand mold their actuators. Our team set out to design an entirely 3D printed soft robotic hand, powered by a pneumatic control system which will prove both the capabilities of soft robots and those of 3D printing. Through research, computer aided design, finite element analysis, and experimental testing, a functioning actuator was created capable of a deflection of 2.17” at a maximum pressure input of 15 psi. The single actuator was expanded into a 4 finger gripper and the design was printed and assembled. The created prototype was ultimately able to lift both a 100-gram apple and a 4-gram pill, proving its functionality in two prominent industries: pharmaceutical and food packing
Discrete Cosserat Approach for Multi-Section Soft Robots Dynamics
In spite of recent progress, soft robotics still suffers from a lack of
unified modeling framework. Nowadays, the most adopted model for the design and
control of soft robots is the piece-wise constant curvature model, with its
consolidated benefits and drawbacks. In this work, an alternative model for
multisection soft robots dynamics is presented based on a discrete Cosserat
approach, which, not only takes into account shear and torsional deformations,
essentials to cope with out-of-plane external loads, but also inherits the
geometrical and mechanical properties of the continuous Cosserat model, making
it the natural soft robotics counterpart of the traditional rigid robotics
dynamics model. The soundness of the model is demonstrated through extensive
simulation and experimental results for both plane and out-of-plane motions.Comment: 13 pages, 9 figure
Learning Ground Traversability from Simulations
Mobile ground robots operating on unstructured terrain must predict which
areas of the environment they are able to pass in order to plan feasible paths.
We address traversability estimation as a heightmap classification problem: we
build a convolutional neural network that, given an image representing the
heightmap of a terrain patch, predicts whether the robot will be able to
traverse such patch from left to right. The classifier is trained for a
specific robot model (wheeled, tracked, legged, snake-like) using simulation
data on procedurally generated training terrains; the trained classifier can be
applied to unseen large heightmaps to yield oriented traversability maps, and
then plan traversable paths. We extensively evaluate the approach in simulation
on six real-world elevation datasets, and run a real-robot validation in one
indoor and one outdoor environment.Comment: Webpage: http://romarcg.xyz/traversability_estimation
DoorGym: A Scalable Door Opening Environment And Baseline Agent
In order to practically implement the door opening task, a policy ought to be
robust to a wide distribution of door types and environment settings.
Reinforcement Learning (RL) with Domain Randomization (DR) is a promising
technique to enforce policy generalization, however, there are only a few
accessible training environments that are inherently designed to train agents
in domain randomized environments. We introduce DoorGym, an open-source door
opening simulation framework designed to utilize domain randomization to train
a stable policy. We intend for our environment to lie at the intersection of
domain transfer, practical tasks, and realism. We also provide baseline
Proximal Policy Optimization and Soft Actor-Critic implementations, which
achieves success rates between 0% up to 95% for opening various types of doors
in this environment. Moreover, the real-world transfer experiment shows the
trained policy is able to work in the real world. Environment kit available
here: https://github.com/PSVL/DoorGym/Comment: Full version (Real world transfer experiments result
Virtual Reality Games for Motor Rehabilitation
This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
Development of a Fabrication Technique for Soft Planar Inflatable Composites
Soft robotics is a rapidly growing field in robotics that combines aspects of biologically inspired characteristics to unorthodox methods capable of conforming and/or adapting to unknown tasks or environments that would otherwise be improbable or complex with conventional robotic technologies. The field of soft robotics has grown rapidly over the past decade with increasing popularity and relevance to real-world applications. However, the means of fabricating these soft, compliant and intricate robots still poses a fundamental challenge, due to the liberal use of soft materials that are difficult to manipulate in their original state such as elastomers and fabric. These material properties rely on informal design approaches and bespoke fabrication methods to build soft systems. As such, there are a limited variety of fabrication techniques used to develop soft robots which hinders the scalability of robots and the time to manufacture, thus limiting their development.
This research focuses towards developing a novel fabrication method for constructing soft planar inflatable composites. The fundamental method is based on a sub-set of additive manufacturing known as composite layering. The approach is designed from a planar manner and takes layers of elastomeric materials, embedded strain-limiting and mask layers. These components are then built up through a layer-by-layer fabrication method with the use of a bespoke film applicator set-up. This enables the fabrication of millimetre-scale soft inflatable composites with complex integrated masks and/or strain-limiting layers. These inflatable composites can then be cut into a desired shape via laser cutting or ablation. A design approach was also developed to expand the functionality of these inflatable composites through modelling and simulation via finite element analysis. Proof of concept prototypes were designed and fabricated to enable pneumatic driven actuation in the form of bending soft actuators, adjustable stiffness sensor, and planar shape change. This technique highlights the feasibility of the fabrication method and the value of its use in creating multi-material composite soft actuators which are thin, compact, flexible, and stretchable and can be applicable towards real-world application
Constructing living buildings: a review of relevant technologies for a novel application of biohybrid robotics
Biohybrid robotics takes an engineering approach to the expansion and exploitation of biological behaviours for application to automated tasks. Here, we identify the construction of living buildings and infrastructure as a high-potential application domain for biohybrid robotics, and review technological advances relevant to its future development. Construction, civil infrastructure maintenance and building occupancy in the last decades have comprised a major portion of economic production, energy consumption and carbon emissions. Integrating biological organisms into automated construction tasks and permanent building components therefore has high potential for impact. Live materials can provide several advantages over standard synthetic construction materials, including self-repair of damage, increase rather than degradation of structural performance over time, resilience to corrosive environments, support of biodiversity, and mitigation of urban heat islands. Here, we review relevant technologies, which are currently disparate. They span robotics, self-organizing systems, artificial life, construction automation, structural engineering, architecture, bioengineering, biomaterials, and molecular and cellular biology. In these disciplines, developments relevant to biohybrid construction and living buildings are in the early stages, and typically are not exchanged between disciplines. We, therefore, consider this review useful to the future development of biohybrid engineering for this highly interdisciplinary application.publishe
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