Realization of human-robot collaboration in hybrid assembly systems by using wearable technology

Çoban, Mustafa; Gelen, Gökhan

doi:10.1109/ceit.2018.8751814

Cited by 7 publications

(10 citation statements)

References 13 publications

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“…For interaction devices, the Human-Robots Collaboration system usually incorporates various periphery devices for interaction depending on the task requirement based on the mechanical architecture of the robots. For instance, wearable devices may be attached to recognize the end of human operations for the sake of protecting human workers [13], and robotic skin can be utilized to provide direct feedback of human co-workers' information [14]. Distinctive from Human-AI Collaboration, Human-Robots Collaboration systems focus more on the physical position or posture of the human collaborators, which is why their peripheral devices are so diversiform.…”

Section: Human-robots Collaborationmentioning

confidence: 99%

Researches advanced in human-computer collaboration and human-machine cooperation: from variances to common prospect

Zhang

2022

2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022)

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The booming technology of artificial intelligence (AI) and robotics enable people not only prospect its huge potential, but also limitation of capability when solving inplicit problems comparing with human. As a result, fields like Human- Computer Collaboration (HCC) and Human-Machine Cooperation (HMC) are developed and explored, with relevant concepts such as Human-in-The-Loop (HiTL) being aroused. Whereas, such types of research areas are lack of uniform standards and procedures, even measurements, attributing to the way too specific works to scenarios. Thus in this paper, a review of Human-Computer Collaboration (HCC) and Human-Machine Cooperation (HMC) is conducted from the aspects of vaiances to their common prospects. From data gathering to decision making and support, finally to interaction interface, the processing and operation of HCC/HMC systems are discussed, with key issues like trust level to agents proposed and future works suggested.

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Section: Human-robots Collaborationmentioning

confidence: 99%

Researches advanced in human-computer collaboration and human-machine cooperation: from variances to common prospect

Zhang

2022

2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022)

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“…Conventional HRI [1][2][3][4][5][6][7] Janken robot [19,20] -High-speed Our goal -High-speed -High-accuracy Current HRI [8][9][10][11][12][13][14][15][16][17][18] The rest of this paper is organized as follows; Section 2 explains the developed Human-Robot collaborative system, Section 3 describes the proposed strategy for Human-Robot collaboration, Section 4 discusses the stability and the collaborative error, Section 5 shows the experimental results of collaborative motion and discusses the frame rate of the collaborative system, Sections 6 explains the analysis and experimental results of the collaborative peg-in-hole task and Section 7 summarizes the conclusions obtained in this work.…”

Section: Accuracymentioning

confidence: 99%

“…Teke et al proposed a method for real-time and robust collaborative robot motion control by using Kinect ® v2 [ 9 ]. Çoban and Gelen achieved an assembly task with Human-Robot collaboration using a wearable device and shortened the operation time of the assembly task [ 10 ]. Wang et al proposed a framework of a TLC (teaching–learning–collaboration) model for performing Human-Robot collaborative tasks and verified the effectiveness of the proposed method [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Development of a Real-Time Human-Robot Collaborative System Based on 1 kHz Visual Feedback Control and Its Application to a Peg-in-Hole Task

Yamakawa

Matsui

Ishikawa

2021

Sensors

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In this research, we focused on Human-Robot collaboration. There were two goals: (1) to develop and evaluate a real-time Human-Robot collaborative system, and (2) to achieve concrete tasks such as collaborative peg-in-hole using the developed system. We proposed an algorithm for visual sensing and robot hand control to perform collaborative motion, and we analyzed the stability of the collaborative system and a so-called collaborative error caused by image processing and latency. We achieved collaborative motion using this developed system and evaluated the collaborative error on the basis of the analysis results. Moreover, we aimed to realize a collaborative peg-in-hole task that required a system with high speed and high accuracy. To achieve this goal, we analyzed the conditions required for performing the collaborative peg-in-hole task from the viewpoints of geometric, force and posture conditions. Finally, in this work, we show the experimental results and data of the collaborative peg-in-hole task, and we examine the effectiveness of our collaborative system.

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“…Coban and Gelen [45] found that human-robot teams performed better than robots on their own. Several authors found that operators preferred autonomous and proactive robots over reactive ones [35,68].…”

Section: Test Resultsmentioning

confidence: 99%

“…Freq. Intention recognition 51 [11, 15, 16, 22, 29, 31, 34, 35, 37, 38, 40-42, 46, 48, 53, 54, 56, 57, 64-66, 68, 69, 73, 74, 77, 80, 85, 88-90, 94, 97, 98, 102, 104-116, 118, 125] Visual Tracking Test 48 [10, 12, 19, 20, 22, 25, 29, 30, 32, 33, 36, 38, 40, 43-48, 56, 61, 63, 64, 67, 70, 74, 76, 77, 79, 83, 85, 91-93, 95-97, 99-101, 105, 108, 111, 112, 115, 117, 118, 123] Motion planning 32 [2,6,10,12,15,31,34,35,37,41,42,48,54,56,57,63,67,73,74,76,77,88,90,91,94,96,97,99,102,105,110,115] Collaboration planning 23 [10, 33-35, 38-41, 43, 47, 48, 58, 65, 66, 68, 69, 71, 83, 84, 104, 105, 114, 125] Collaborative heavy lifting 18 [1-4, 6, 12, 14, 18, 22, 28, 47, 55, 56, 71, 79, 84, 104, 125] Test control system [5,8,9,27,30,50,79,111,114] Performance assessment [45,51,…”

Section: Research Objectivesmentioning

confidence: 99%

Human-Robot Trust Assessment From Physical Apprehension Signals

Hald

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show abstract

Realization of human-robot collaboration in hybrid assembly systems by using wearable technology

Cited by 7 publications

References 13 publications

Researches advanced in human-computer collaboration and human-machine cooperation: from variances to common prospect

Researches advanced in human-computer collaboration and human-machine cooperation: from variances to common prospect

Development of a Real-Time Human-Robot Collaborative System Based on 1 kHz Visual Feedback Control and Its Application to a Peg-in-Hole Task

Human-Robot Trust Assessment From Physical Apprehension Signals

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