scholarly journals Design and Control of a Open-Source, Low Cost, 3D Printed Dynamic Quadruped Robot

2021 ◽  
Vol 11 (9) ◽  
pp. 3762
Author(s):  
Joonyoung Kim ◽  
Taewoong Kang ◽  
Dongwoon Song ◽  
Seung-Joon Yi

In this paper, we present a new open source dynamic quadruped robot, PADWQ (pronounced pa-dook), which features 12 torque controlled quasi direct drive joints with high control bandwidth, as well as onboard depth sensor and GPU-equipped computer that allows for a highly dynamic locomotion over uncertain terrains. In contrast to other dynamic quadruped robots based on custom actuator and machined metal structural parts, the PADWQ is entirely built from off the shelf components and standard 3D printed plastic structural parts, which allows for a rapid distribution and duplication without the need for advanced machining process. To make sure that the plastic structural parts can withstand the stress of dynamic locomotion, we performed finite element analysis (FEA) on leg structural parts as well as a continuous walking test using the physical robot, both of which the robot has passed successfully. We hope this work to help a wide range of researchers and engineers that need an affordable, highly capable and easily customizable quadruped robot.

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 572
Author(s):  
Mads Jochumsen ◽  
Taha Al Muhammadee Janjua ◽  
Juan Carlos Arceo ◽  
Jimmy Lauber ◽  
Emilie Simoneau Buessinger ◽  
...  

Brain-computer interfaces (BCIs) have been proven to be useful for stroke rehabilitation, but there are a number of factors that impede the use of this technology in rehabilitation clinics and in home-use, the major factors including the usability and costs of the BCI system. The aims of this study were to develop a cheap 3D-printed wrist exoskeleton that can be controlled by a cheap open source BCI (OpenViBE), and to determine if training with such a setup could induce neural plasticity. Eleven healthy volunteers imagined wrist extensions, which were detected from single-trial electroencephalography (EEG), and in response to this, the wrist exoskeleton replicated the intended movement. Motor-evoked potentials (MEPs) elicited using transcranial magnetic stimulation were measured before, immediately after, and 30 min after BCI training with the exoskeleton. The BCI system had a true positive rate of 86 ± 12% with 1.20 ± 0.57 false detections per minute. Compared to the measurement before the BCI training, the MEPs increased by 35 ± 60% immediately after and 67 ± 60% 30 min after the BCI training. There was no association between the BCI performance and the induction of plasticity. In conclusion, it is possible to detect imaginary movements using an open-source BCI setup and control a cheap 3D-printed exoskeleton that when combined with the BCI can induce neural plasticity. These findings may promote the availability of BCI technology for rehabilitation clinics and home-use. However, the usability must be improved, and further tests are needed with stroke patients.


2018 ◽  
Vol 65 (5) ◽  
pp. 412-419 ◽  
Author(s):  
Claudia R. Cutler ◽  
Anita L. Hamilton ◽  
Emma Hough ◽  
Cheyenne M. Baines ◽  
Ross A. Clark

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3144 ◽  
Author(s):  
Sherif Said ◽  
Ilyes Boulkaibet ◽  
Murtaza Sheikh ◽  
Abdullah S. Karar ◽  
Samer Alkork ◽  
...  

In this paper, a customizable wearable 3D-printed bionic arm is designed, fabricated, and optimized for a right arm amputee. An experimental test has been conducted for the user, where control of the artificial bionic hand is accomplished successfully using surface electromyography (sEMG) signals acquired by a multi-channel wearable armband. The 3D-printed bionic arm was designed for the low cost of 295 USD, and was lightweight at 428 g. To facilitate a generic control of the bionic arm, sEMG data were collected for a set of gestures (fist, spread fingers, wave-in, wave-out) from a wide range of participants. The collected data were processed and features related to the gestures were extracted for the purpose of training a classifier. In this study, several classifiers based on neural networks, support vector machine, and decision trees were constructed, trained, and statistically compared. The support vector machine classifier was found to exhibit an 89.93% success rate. Real-time testing of the bionic arm with the optimum classifier is demonstrated.


Author(s):  
A. Elibiary ◽  
W. Oakey ◽  
S. Jun ◽  
B. Sanz-Izquierdo ◽  
D. Bird ◽  
...  

2020 ◽  
Author(s):  
Matthew Wincott ◽  
Andrew Jefferson ◽  
Ian M. Dobbie ◽  
Martin J. Booth ◽  
Ilan Davis ◽  
...  

ABSTRACTCommercial fluorescence microscope stands and fully automated XYZt fluorescence imaging systems are generally beyond the limited budgets available for teaching and outreach. We have addressed this problem by developing “Microscopi”, an accessible, affordable, DIY automated imaging system that is built from 3D printed and commodity off-the-shelf hardware, including electro-mechanical, computer and optical components. Our design features automated sample navigation and image capture with a simple web-based graphical user interface, accessible with a tablet or other mobile device. The light path can easily be switched between different imaging modalities. The open source Python-based control software allows the hardware to be driven as an integrated imaging system. Furthermore, the microscope is fully customisable, which also enhances its value as a learning tool. Here, we describe the basic design and demonstrate imaging performance for a range of easily sourced specimens.HighlightsPortable, low cost, self-build from 3D printed and commodity componentsMultimodal imaging: bright field, dark field, pseudo-phase and fluorescenceAutomated XYZt imaging from a tablet or smartphone via a simple GUIWide ranging applications in teaching, outreach and fieldworkOpen source hardware and software design, allowing user modification


2021 ◽  
Vol 13 (22) ◽  
pp. 12807
Author(s):  
Md Fahim Tanvir Hossain ◽  
Samer Dessouky ◽  
Ayetullah B. Biten ◽  
Arturo Montoya ◽  
Daniel Fernandez

This study aims at designing and developing a new technique to harvest solar energy from asphalt pavements. The proposed energy harvester system consists of a pavement solar box with a transparent polycarbonate sample and a thin-film solar panel. This device mechanism can store energy in a battery charged over daytime and later convert it into electric power as per demand. A wide range of polycarbonate samples containing different thicknesses, elastic moduli, and light transmission properties were tested to select the most efficient materials for the energy harvester system. Transmittance Spectroscopy was conducted to determine the percent light transmission property of the polycarbonate samples at different wavelengths in the visible spectrum. Finite Element Analysis modeling of the pavement–tire load system was conducted to design the optimal energy harvester system under static load. It was followed by the collection of data on the generated power under different weather conditions. The energy harvesters were also subjected to vehicular loads in the field. The results suggest that the proposed pavement solar box can generate an average of 23.7 watts per square meter continuously over 6 h a day under sunny conditions for the weather circumstances encountered in South Texas while providing a slightly smaller power output in other weather circumstances. It is a promising self-powered and low-cost installation technique that can be implemented at pedestrian crossings and intersections to alert distracted drivers at the time of pedestrian crossing, which is likely to improve pedestrian safety.


Polymers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 3555
Author(s):  
Patrich Ferretti ◽  
Gian Maria Santi ◽  
Christian Leon-Cardenas ◽  
Elena Fusari ◽  
Giampiero Donnici ◽  
...  

Additive manufacturing processes have evolved considerably in the past years, growing into a wide range of products through the use of different materials depending on its application sectors. Nevertheless, the fused deposition modelling (FDM) technique has proven to be an economically feasible process turning additive manufacture technologies from consumer production into a mainstream manufacturing technique. Current advances in the finite element method (FEM) and the computer-aided engineering (CAE) technology are unable to study three-dimensional (3D) printed models, since the final result is highly dependent on processing and environment parameters. Because of that, an in-depth understanding of the printed geometrical mesostructure is needed to extend FEM applications. This study aims to generate a homogeneous structural element that accurately represents the behavior of FDM-processed materials, by means of a representative volume element (RVE). The homogenization summarizes the main mechanical characteristics of the actual 3D printed structure, opening new analysis and optimization procedures. Moreover, the linear RVE results can be used to further analyze the in-deep behavior of the FDM unit cell. Therefore, industries could perform a feasible engineering analysis of the final printed elements, allowing the FDM technology to become a mainstream, low-cost manufacturing process in the near future.


Author(s):  
Sachin Bijadi ◽  
Erik de Bruijn ◽  
Erik Y. Tempelman ◽  
Jos Oberdorf

Low-cost 3D desktop printing, although still in its infancy, is rapidly maturing, with a wide range of applications. With its ease of production and affordability, it has led to development of a global maker culture, with the design and manufacture of artefacts by individuals as a collaborative & creative hobbyist practice. This has enabled mass customization of goods with the potential to disrupt conventional manufacturing, giving more people access to traditionally expensive products like prosthetics and medical devices [1], as is the case with e-NABLE, a global community providing open source prosthetics for people with upper limb deficiencies. However one of the major barriers to proliferation of 3D printing as a major manufacturing method is the limitation of compatible materials for use with the technology [2]. This places constraints on the design approach, as well as the complexity & functionality of artefacts that can be produced with 3D printing as compared to traditional manufacturing methods. As a result, devices like the e-NABLE Raptor Reloaded prosthetic hand, which is designed specifically to be produced via a single extruder FDM desktop 3D printer, have limited functionality as compared to conventional prosthetics, leading to low active use and prosthesis abandonment [3]. However, with the advent of multi-material desktop 3D printing, and increasing availability of a broader range of compatible materials (of varying characteristics) [2], there is scope for improving capabilities of low-cost prosthetics through the creation of more sophisticated multi-material functional integrated devices. This work documents the exploration of potential applications of multi-material 3D printing to improve production, capabilities and usability of low-cost open source prosthetics. Various material combinations were initially studied and functional enhancements for current 3D printed prosthetics were prototyped using key material combinations identified. Further, a user-centered design approach was utilized to develop a novel multi-material anthropomorphic prosthetic hand ‘ex_machina’ based on a modular platform architecture, to demonstrate the scope for reduced build complexity and improved dexterity & functional customization enabled by dual extrusion FDM desktop 3D printing. A full prototype was built & tested with a lead user, and results analyzed to determine scope for optimization.


Author(s):  
Joonyoung Kim ◽  
Taewoong Kang ◽  
Dongwoon Song ◽  
Seung-Joon Yi
Keyword(s):  
Low Cost ◽  

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