Robot teleoperation via motion mapping has been demonstrated to be an efficient and intuitive approach for controlling and teaching the whole-body motion coordination of humanoid robots. However, the physical fatigue ...
Robot teleoperation via motion mapping has been demonstrated to be an efficient and intuitive approach for controlling and teaching the whole-body motion coordination of humanoid robots. However, the physical fatigue in the usage of such robot teleoperation interfaces may prevent this approach to be widely used in large scale by diverse workforce populations. As a result, this paper conducts a user study to investigate the physical fatigue of teleoperators in the whole-body motion mapping teleoperation of a mobile humanoid assistive robot. Through a Vicon motion capture system, participants teleoperated the robot to perform general purpose assistive tasks that involve reaching-to-grasp, bimanual manipulation, loco-manipulation and human-robot interaction. We assess the physical fatigue based on surface electromyography (sEMG) measurement, and compare it between different tasks and muscles. Our analysis results indicate that: (1) Fatigue happens more in the tasks that involve more precise manipulation and steady posture maintenance; (2) Deltoids, Biceps and Trapezius are used more for such tasks and thus have more fatigue than others. These findings imply that automating the fatigue-causing task components may reduce the physical fatigue in motion mapping teleoperation.
The 2004 Aceh tsunami triggered by a major earthquake taught us the importance of disaster mitigation efforts, one of which is monitoring seismic activity using earthquake sensors. However, the success of these sensor...
The 2004 Aceh tsunami triggered by a major earthquake taught us the importance of disaster mitigation efforts, one of which is monitoring seismic activity using earthquake sensors. However, the success of these sensors is highly dependent on community involvement, awareness, and active maintenance of the technology. This study aims to examine the perceptions of the Acehnese community regarding earthquake sensors and to identify factors that influence their perceptions of this disaster mitigation technology. The study was conducted in six districts in Aceh Province: Aceh Besar, Aceh Selatan, Aceh Singkil, Aceh Utara, Lhokseumawe, and Aceh Tengah, which were selected due to their high seismic activity and the installation of existing earthquake sensors. The study involved 112 respondents who completed a questionnaire to assess their knowledge, perceptions, and attitudes toward sensors. A One Sample T-Test was used to assess each factor influenced perceptions. The study showed that experience was the most influential factor in shaping perceptions, indicating that individuals directly involved in installing the sensors were more likely to appreciate their benefits. This study emphasizes the importance of more targeted educational campaign efforts that emphasize the role and importance of earthquake sensors in reducing earthquake risk and bridging the gap in public understanding of earthquake sensors. By directly involving the community in installing or maintaining earthquake sensors, it can improve their perception and increase the effectiveness of disaster preparedness strategies.
This paper presents the development of instrumentation for the measurement of high-temperature thermal conductivity of bulk and coatings using a modulated photothermal radiometry (MPR) method, where a sample is heated...
详细信息
Line following robots are becoming increasingly popular both in industrial and in domestic applications. In these real world environments, noisy or inaccurate measurements lead to ambiguous conclusions about the robot...
详细信息
The present paper features a mathematical model of load capacity and static characteristics calculation of foil gas dynamic bearings with conical surfaces lubricated with cryogenic fluids based on equations of thermop...
详细信息
We have investigated the effects of alternate current poling (ACP) for four different plates of [100]-oriented (100-x)Pb(Mg1/3Nb2/3)O3-xPbTiO3 (PMN-xPT, x = 28, 29, 30, 31) single crystals (SCs) obtained from one ingo...
详细信息
Due to its numerous properties, iron is one of the most useful materials on the planet. The mechanical and physical properties of iron and its alloys are suitable and manageable. These alloys have significant issues l...
Due to its numerous properties, iron is one of the most useful materials on the planet. The mechanical and physical properties of iron and its alloys are suitable and manageable. These alloys have significant issues like heavyweight, low corrosion resistivity and some other limitations. The researchers and companies for solving problems look out for other alternative materials. Titanium and its alloys, according to the researchers, have a huge variety of engineering applications. Titanium and titanium alloys have high strength and corrosion resistance, and they perform well at high temperatures up to nearly 600 °C. Titanium and its alloys have a density of about 60 % that of steel and its alloys, and about 50 % that of nickel alloys. Even though titanium and its alloys have cost and supply problems, they're utilized in numerous industries, which includes aerospace, automotive, and navy projects. Titanium and its alloys have unique properties, indicating that they are cost-effective components that require special manufacturing techniques. This study aims to explore the potential of titanium and its alloys to replace iron in various engineering applications. Addressing the critical need for materials with superior performance characteristics is essential for advancing technological development.
The mechatronic device has been designed and implemented based on the comprehensive rehabilitation of the paretic upper limb. This system has been prepared for an individual approach to the recovery process including ...
详细信息
Metal-organic frameworks (MOFs) are a novel class of porous materials that combine organic linkers and inorganic metal ions. Supercapacitors use a large specific surface area, adjustable architecture, and tunable poro...
详细信息
Metal-organic frameworks (MOFs) are a novel class of porous materials that combine organic linkers and inorganic metal ions. Supercapacitors use a large specific surface area, adjustable architecture, and tunable porosity and pore diameters to improve the electrochemical performances with metal sulfides. The main goal of this study was to make a nickel oxide ternary composite using a hydrothermal method with urea as a catalyst for electrochemical uses. We characterized these fabricated composite materials using analytical and morphological characterization for their confirmation. These results show that the composite electrode had a great specific capacitance of 464 F/g at 0.5 A/g in a 1 M KOH electrolyte when set up with three electrodes. The symmetric two-electrode system showed 52.83 F/g at 0.5 A/g with an excellent energy density of 13.14 Whkg −1 and a power density of 616 Wkg −1 via 1 M KOH electrolyte. The fabricated ternary composite electrode demonstrated cyclic stability, with an excellent retention rate of 89 % after 7000 cycles. Therefore, the fabricated ternary composite electrode materials have enormous potential for electrochemical storage properties.
Magnetorheological elastomers (MRE) have gained popularity due to their ability to control viscoelastic properties by varying the strength of the magnetic field. Due to the obvious nonlinear and complex behavior of MR...
Magnetorheological elastomers (MRE) have gained popularity due to their ability to control viscoelastic properties by varying the strength of the magnetic field. Due to the obvious nonlinear and complex behavior of MRE, machine learning approaches were used to predict the MRE viscoelastic properties, which are storage and loss modulus. In comparison to the traditional viscoelastic model, which is complex in mathematical derivation, machine learning method easily identifies trends and patterns by mapping the input-output relationship. It can also handle nonlinear problems by training on data. Support vector regression (SVR), Gaussian process regression (GPR), Backpropagation neural network (BP-ANN), and Extreme learning machine (ELM) were introduced and compared to simulate the field-dependent viscoelastic behavior of MRE with frequency and magnetic field strength as model input. As a result, the ELM model produced the highest accuracy, with more than 98 percent accuracy on model generalization capability. Therefore, this demonstrates that machine learning can replace traditional modelling approaches and serve as a basis for material and device development.
暂无评论