Design and Evaluation of Human-Machine Interface for NEXUS: A Custom Microassembly System

Author(s):  
Danming Wei ◽  
Mariah B. Hall ◽  
Andriy Sherehiy ◽  
Sumit Kumar Das ◽  
Dan O. Popa

Abstract Microassembly systems utilizing precision robotics have long been used for realizing 3-dimensional microstructures such as microrobots. Prior to assembly, such components are fabricated using Micro-Electro-Mechanical-System (MEMS) technology. The microassembly system then directs a microgripper through automated or human-controlled pick-and-place operations. In this paper, we describe a novel custom microassembly system, named NEXUS. The NEXUS integrates multi-degree of freedom (DOF) precision positioners, microscope computer vision, and micro-scale process tools such as a microgripper and vacuum tip. A semi-autonomous human-machine interface (HMI) is programmed by NI LabVIEW® to allow the operator to interact with the microassembly system. The NEXUS human-machine interface includes multiple functions, such as positioning, target detection, visual servoing, and inspection. The microassembly system’s HMI was used by operators to assemble various 3-dimensional microrobots such as the Solarpede, a novel light-powered stick-and-slip mobile microcrawler. Experimental results are reported in this paper that evaluate the system’s semi-autonomous capabilities in terms of assembly rate and yield and compare them to purely teleoperated assembly performance. Results show that the semi-automated capabilities of the microassembly system’s HMI offer a more consistent assembly rate of microrobot components.

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
Danming Wei ◽  
Mariah B. Hall ◽  
Andriy Sherehiy ◽  
Dan O. Popa

Abstract Microassembly systems utilizing precision robotics have long been used for realizing three-dimensional microstructures such as microsystems and microrobots. Prior to assembly, microscale components are fabricated using micro-electromechanical-system (MEMS) technology. The microassembly system then directs a microgripper through a series of automated or human-controlled pick-and-place operations. In this paper, we describe a novel custom microassembly system, named NEXUS, that can be used to prototype MEMS microrobots. The NEXUS integrates multi-degrees-of-freedom (DOF) precision positioners, microscope computer vision, and microscale process tools such as a microgripper and vacuum tip. A semi-autonomous human–machine interface (HMI) was programmed to allow the operator to interact with the microassembly system. The NEXUS human–machine interface includes multiple functions, such as positioning, target detection, visual servoing, and inspection. The microassembly system's HMI was used by operators to assemble various three-dimensional microrobots such as the Solarpede, a novel light-powered stick-and-slip mobile microcrawler. Experimental results are reported in this paper to evaluate the system's semi-autonomous capabilities in terms of assembly rate and yield and compare them to purely teleoperated assembly performance. Results show that the semi-automated capabilities of the microassembly system's HMI offer a more consistent assembly rate of microrobot components and are less reliant on the operator's experience and skill.


1990 ◽  
Author(s):  
B. Bly ◽  
P. J. Price ◽  
S. Park ◽  
S. Tepper ◽  
E. Jackson ◽  
...  

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 687
Author(s):  
Jinzhen Dou ◽  
Shanguang Chen ◽  
Zhi Tang ◽  
Chang Xu ◽  
Chengqi Xue

With the development and promotion of driverless technology, researchers are focusing on designing varied types of external interfaces to induce trust in road users towards this new technology. In this paper, we investigated the effectiveness of a multimodal external human–machine interface (eHMI) for driverless vehicles in virtual environment, focusing on a two-way road scenario. Three phases of identifying, decelerating, and parking were taken into account in the driverless vehicles to pedestrian interaction process. Twelve eHMIs are proposed, which consist of three visual features (smile, arrow and none), three audible features (human voice, warning sound and none) and two physical features (yielding and not yielding). We conducted a study to gain a more efficient and safer eHMI for driverless vehicles when they interact with pedestrians. Based on study outcomes, in the case of yielding, the interaction efficiency and pedestrian safety in multimodal eHMI design was satisfactory compared to the single-modal system. The visual modality in the eHMI of driverless vehicles has the greatest impact on pedestrian safety. In addition, the “arrow” was more intuitive to identify than the “smile” in terms of visual modality.


Author(s):  
Saverio Trotta ◽  
Dave Weber ◽  
Reinhard W. Jungmaier ◽  
Ashutosh Baheti ◽  
Jaime Lien ◽  
...  

Procedia CIRP ◽  
2021 ◽  
Vol 100 ◽  
pp. 488-493
Author(s):  
Florian Beuss ◽  
Frederik Schmatz ◽  
Marten Stepputat ◽  
Fabian Nokodian ◽  
Wilko Fluegge ◽  
...  

Nanoscale ◽  
2021 ◽  
Author(s):  
Qiufan Wang ◽  
Jiaheng Liu ◽  
Guofu Tian ◽  
Daohong Zhang

The rapid development of human-machine interface and artificial intelligence is dependent on flexible and wearable soft devices such as sensors and energy storage systems. One of the key factors for...


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3731
Author(s):  
Maik Bertke ◽  
Ina Kirsch ◽  
Erik Uhde ◽  
Erwin Peiner

To monitor airborne nano-sized particles (NPs), a single-chip differential mobility particle sizer (DMPS) based on resonant micro cantilevers in defined micro-fluidic channels (µFCs) is introduced. A size bin of the positive-charged fraction of particles herein is separated from the air stream by aligning their trajectories onto the cantilever under the action of a perpendicular electrostatic field of variable strength. We use previously described µFCs and piezoresistive micro cantilevers (PMCs) of 16 ng mass fabricated using micro electro mechanical system (MEMS) technology, which offer a limit of detection of captured particle mass of 0.26 pg and a minimum detectable particulate mass concentration in air of 0.75 µg/m3. Mobility sizing in 4 bins of a nebulized carbon aerosol NPs is demonstrated based on finite element modelling (FEM) combined with a-priori knowledge of particle charge state. Good agreement of better than 14% of mass concentration is observed in a chamber test for the novel MEMS-DMPS vs. a simultaneously operated standard fast mobility particle sizer (FMPS) as reference instrument. Refreshing of polluted cantilevers is feasible without de-mounting the sensor chip from its package by multiply purging them alternately in acetone steam and clean air.


2021 ◽  
Vol 13 (8) ◽  
pp. 188
Author(s):  
Marianna Di Gregorio ◽  
Marco Romano ◽  
Monica Sebillo ◽  
Giuliana Vitiello ◽  
Angela Vozella

The use of Unmanned Aerial Systems, commonly called drones, is growing enormously today. Applications that can benefit from the use of fleets of drones and a related human–machine interface are emerging to ensure better performance and reliability. In particular, a fleet of drones can become a valuable tool for monitoring a wide area and transmitting relevant information to the ground control station. We present a human–machine interface for a Ground Control Station used to remotely operate a fleet of drones, in a collaborative setting, by a team of multiple operators. In such a collaborative setting, a major interface design challenge has been to maximize the Team Situation Awareness, shifting the focus from the individual operator to the entire group decision-makers. We were especially interested in testing the hypothesis that shared displays may improve the team situation awareness and hence the overall performance. The experimental study we present shows that there is no difference in performance between shared and non-shared displays. However, in trials when unexpected events occurred, teams using shared displays-maintained good performance whereas in teams using non-shared displays performance reduced. In particular, in case of unexpected situations, operators are able to safely bring more drones home, maintaining a higher level of team situational awareness.


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