GUI Teaching Pendant Development for a 6 Axis Articulated Robot

Kaluarachchi, Malaka Miyuranga; Annaz, Fawaz Y.

doi:10.1007/978-3-642-35197-6_12

“…where (1) and (2) denote the probability distribution of the two batches of selected examples belonging to each label, respectively. Attention Mechanisms: Attention mechanisms play an important role in human perception, and many studies [32][33][34] have embedded attention mechanisms in convolutional neural networks to improve performance.…”

Section: Bhand Gesture Recognitionmentioning

confidence: 99%

An Online Robot Teaching Method using Static Hand Gestures and Poses

Sun¹,

Zhang²,

Chen³

et al. 2021

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0

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With an increasing number of robots are employed in manufacturing, a human-robot interaction method that can teach robots in a natural, accurate, and rapid manner is needed. In this paper, we propose a novel human-robot interface based on the combination of static hand gestures and hand poses. In our proposed interface, the pointing direction of the index finger and the orientation of the whole hand are extracted to indicate the moving direction and orientation of the robot in a fast-teaching mode. A set of hand gestures are designed according to their usage in humans' daily life and recognized to control the position and orientation of the robot in a fine-teaching mode. We employ the feature extraction ability of the hand pose estimation network via transfer learning and utilize attention mechanisms to improve the performance of the hand gesture recognition network. The inputs of hand pose estimation and hand gesture recognition networks are monocular RGB images, making our method independent of depth information input and applicable to more scenarios. In the regular shape reconstruction experiments on the UR3 robot, the mean error of the reconstructed shape is less than 1 mm, which demonstrates the effectiveness and efficiency of our method.

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“…where (1) and (2) denote the probability distribution of the two batches of selected examples belonging to each label, respectively. Attention Mechanisms: Attention mechanisms play an important role in human perception, and many studies [32][33][34] have embedded attention mechanisms in convolutional neural networks to improve performance.…”

Section: Bhand Gesture Recognitionmentioning

confidence: 99%

An Online Robot Teaching Method using Static Hand Gestures and Poses

Sun¹,

Zhang²,

Chen³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

With an increasing number of robots are employed in manufacturing, a human-robot interaction method that can teach robots in a natural, accurate, and rapid manner is needed. In this paper, we propose a novel human-robot interface based on the combination of static hand gestures and hand poses. In our proposed interface, the pointing direction of the index finger and the orientation of the whole hand are extracted to indicate the moving direction and orientation of the robot in a fast-teaching mode. A set of hand gestures are designed according to their usage in humans' daily life and recognized to control the position and orientation of the robot in a fine-teaching mode. We employ the feature extraction ability of the hand pose estimation network via transfer learning and utilize attention mechanisms to improve the performance of the hand gesture recognition network. The inputs of hand pose estimation and hand gesture recognition networks are monocular RGB images, making our method independent of depth information input and applicable to more scenarios. In the regular shape reconstruction experiments on the UR3 robot, the mean error of the reconstructed shape is less than 1 mm, which demonstrates the effectiveness and efficiency of our method.

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“…Having the ability to remotely program a robot outside of scheduled lab times can allow more students the opportunity to gain experience using a teach pendant. Kaluarachchi et al present a soft pendant for a 6-axis Yaskawa Motoman HP3J robot [13]. Abbas et al present the idea of an augmented reality based teaching pendant using a smart phone [14].…”

mentioning

confidence: 99%

Development of Remote Virtual Teach Pendant for Robot Programming: Lessons Learned

Hsieh

¹

2019 ASEE Annual Conference &Amp; Exposition Proceedings

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He holds a joint appointment with the Department of Engineering Technology and the Department of Mechanical Engineering. His research interests include engineering education, cognitive task analysis, automation, robotics and control, intelligent manufacturing system design, and micro/nano manufacturing. He is also the Director of the Rockwell Automation laboratory at Texas A&M University, a stateof-the-art facility for education and research in the areas of automation, control, and automated system integration.

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GUI Teaching Pendant Development for a 6 Axis Articulated Robot

Cited by 7 publications

References 3 publications

An Online Robot Teaching Method using Static Hand Gestures and Poses

An Online Robot Teaching Method using Static Hand Gestures and Poses

An Online Robot Teaching Method using Static Hand Gestures and Poses

Development of Remote Virtual Teach Pendant for Robot Programming: Lessons Learned

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