A Hierarchical Architecture for Human–Robot Cooperation Processes

Darvish, Kourosh; Simetti, Enrico; Mastrogiovanni, Fulvio; Casalino, Giuseppe

doi:10.1109/tro.2020.3033715

Cited by 42 publications

(33 citation statements)

References 55 publications

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“…Such measurement systems are often available from different commercial vendors who specialize in a single measurement system, and establishing a robust software infrastructure to integrate different measurement systems is often a daunting task. This work is realized using a variety of open-source software tools for modeling 7 , heterogeneous measurement data serialization 8 , and estimation algorithms 9 10 that can be set up easily through a meta-repository 11 . A key technical challenge is to realize a single wearable system that combines different measurement modalities 12 and provides a quick and easy- This article has been accepted for publication in a future issue of this journal, but has not been fully edited.…”

Section: Conclusion and Remarksmentioning

confidence: 99%

“…Human-Robot Collaboration (HRC) is an example of complex work scenarios, which is considered to be one of the key enabling technologies that truly holds the potential to usher us through Industry 4.0 [7] [8]. The last decade has seen significant research and development efforts in improving robotic systems that are to be deployed alongside human partners, primarily with the focus on the safety and protection of humans.…”

Section: Introductionmentioning

confidence: 99%

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Online Non-Collocated Estimation of Payload and Articular Stress for Real-Time Human Ergonomy Assessment

et al. 2021

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Improving the quality of work for human beings is receiving a lot of attention from multiple research communities. In particular, digital transformation in human factors and ergonomics is going to empower the next generation of the socio-technical workforce. The use of wearable sensors, collaborative robots, and exoskeletons, coupled with novel technologies for the real-time assessment of human ergonomy forms the crux of this digital transformation. In this direction, this paper focuses on the open problem of estimating the interaction wrench experienced at the human extremities (such as hands), where the feasibility of direct sensor measurements is not practical. We refer to our approach as non-collocated wrench estimation, as we aim to estimate the wrench at known contact locations but without using any direct force-torque sensor measurements at these known locations. We achieve this by extending the formulation of stochastic inverse dynamics for humans by considering a centroidal dynamics constraint to perform a reliable non-collocated estimation of interaction wrench and the joint torques (articular stress) experienced as a direct consequence of the interaction. Our approach of non-collocated estimation is thoroughly validated in terms of payload estimation and articular stress estimation through validation and experimental scenarios involving dynamic human motions like walking.

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Section: Conclusion and Remarksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Online Non-Collocated Estimation of Payload and Articular Stress for Real-Time Human Ergonomy Assessment

et al. 2021

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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%

“…et al constructed a mathematical model and simulation environment of Human-Robot collaboration [ 14 ]. Darvish et al proposed a hierarchical architecture of a Human-Robot cooperative system, showed the algorithms used to evaluate the architecture and performed experiments [ 15 ].…”

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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“…This implies that programming is still done offline, while the robot and the tasks are being prepared, and the actual execution phase is mostly autonomous execution of the robot. While applications can be found ( Sadrfaridpour and Wang, 2017 ; Johannsmeier and Haddadin, 2017 ; Darvish et al, 2021 ) that integrate coordinated actions (e.g., waiting for human input or trigger), still this is pre-programmed and planned to happen at certain specified occurrences. Coordination is thus planned in advance and both agents (i.e., human and robot) act as decided by a fixed protocol.…”

Section: Introductionmentioning

confidence: 99%

Coordinating Shared Tasks in Human-Robot Collaboration by Commands

et al. 2021

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Human-robot collaboration is gaining more and more interest in industrial settings, as collaborative robots are considered safe and robot actions can be programmed easily by, for example, physical interaction. Despite this, robot programming mostly focuses on automated robot motions and interactive tasks or coordination between human and robot still requires additional developments. For example, the selection of which tasks or actions a robot should do next might not be known beforehand or might change at the last moment. Within a human-robot collaborative setting, the coordination of complex shared tasks, is therefore more suited to a human, where a robot would act upon requested commands.In this work we explore the utilization of commands to coordinate a shared task between a human and a robot, in a shared work space. Based on a known set of higher-level actions (e.g., pick-and-placement, hand-over, kitting) and the commands that trigger them, both a speech-based and graphical command-based interface are developed to investigate its use. While speech-based interaction might be more intuitive for coordination, in industrial settings background sounds and noise might hinder its capabilities. The graphical command-based interface circumvents this, while still demonstrating the capabilities of coordination. The developed architecture follows a knowledge-based approach, where the actions available to the robot are checked at runtime whether they suit the task and the current state of the world. Experimental results on industrially relevant assembly, kitting and hand-over tasks in a laboratory setting demonstrate that graphical command-based and speech-based coordination with high-level commands is effective for collaboration between a human and a robot.

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A Hierarchical Architecture for Human–Robot Cooperation Processes

Cited by 42 publications

References 55 publications

Online Non-Collocated Estimation of Payload and Articular Stress for Real-Time Human Ergonomy Assessment

Online Non-Collocated Estimation of Payload and Articular Stress for Real-Time Human Ergonomy Assessment

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

Coordinating Shared Tasks in Human-Robot Collaboration by Commands

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