Gesture-based human-robot interaction for human assistance in manufacturing

Neto, Pedro; Simão, Miguel; Mendes, Nuno; Safeea, Mohammad

doi:10.1007/s00170-018-2788-x

Cited by 118 publications

(64 citation statements)

References 33 publications

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“…In [ 26 ], a system composed by five Inertial Measurement Unit (IMU) sensors is used to recognize human gestures. The IMU sensors are distributed in the upper part of the operator’s body, along with an ultra-wide band positioning system.…”

Section: Robotic Systems and Human-robot Perceptionmentioning

confidence: 99%

Human-Robot Perception in Industrial Environments: A Survey

Bonci

Cheng

Indri

et al. 2021

Sensors

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Perception capability assumes significant importance for human–robot interaction. The forthcoming industrial environments will require a high level of automation to be flexible and adaptive enough to comply with the increasingly faster and low-cost market demands. Autonomous and collaborative robots able to adapt to varying and dynamic conditions of the environment, including the presence of human beings, will have an ever-greater role in this context. However, if the robot is not aware of the human position and intention, a shared workspace between robots and humans may decrease productivity and lead to human safety issues. This paper presents a survey on sensory equipment useful for human detection and action recognition in industrial environments. An overview of different sensors and perception techniques is presented. Various types of robotic systems commonly used in industry, such as fixed-base manipulators, collaborative robots, mobile robots and mobile manipulators, are considered, analyzing the most useful sensors and methods to perceive and react to the presence of human operators in industrial cooperative and collaborative applications. The paper also introduces two proofs of concept, developed by the authors for future collaborative robotic applications that benefit from enhanced capabilities of human perception and interaction. The first one concerns fixed-base collaborative robots, and proposes a solution for human safety in tasks requiring human collision avoidance or moving obstacles detection. The second one proposes a collaborative behavior implementable upon autonomous mobile robots, pursuing assigned tasks within an industrial space shared with human operators.

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Section: Robotic Systems and Human-robot Perceptionmentioning

confidence: 99%

Human-Robot Perception in Industrial Environments: A Survey

Bonci

Cheng

Indri

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…The development and acceptance of collaborative robots are highly dependent on reliable and intuitive human-robot interaction on the factory floor [27]. Authors use wearable sensors and inertial measurement units to capture the human upper body gestures and propose a parameterisation robotic task manager, in which according to the system speech and visual feedback, the co-worker selects/validates robot options using gestures.…”

Section: Collaborative Robotsmentioning

confidence: 99%

Sustainable Move towards Flexible, Robotic, Human-Involving Workplace

2020

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The realisation of the ideas of smart factories and sustainable manufacturing can be quickly realised in companies where industrial production is high-volume, low-mix. However, it is more difficult to follow trends toward industry 4.0 in craft industries such as tooling. This kind of work environment is a challenge for the deployment of sustainability and smart technologies because many stages involve the so-called “manual processing according to the worker’s feeling and experience.” With the help of literature review and testing in the production environment, we approach the design of a procedure for planning a sustainable technological upgrade of craft production. The best method proved to be a combination of a maturity model, process mapping with flowcharts, critical analysis, and customised evaluation model. Workplace flexibility, as a move towards sustainability, is presented in a laboratory environment on screwing performed by human wearing HoloLens and collaborative robot.

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“…The development and the improvement of the technologies used for the design of collaborative robots, together with the reduction of the investment required for their installation, have led to an interesting spread of these systems [11,12]. Recent research has shown how a proper programming of a cobot can be crucial to guarantee a successful use of such a device [13]; other important aspects are related to the used visual system and to the effectiveness of the grasp action [14,15]. For now, most of the investigated applications are related to assembly environments, in which cobots are used to support the operator during the execution of the tasks [16][17][18].…”

Section: Literature Analysismentioning

confidence: 99%

Modelling time efficiency of cobot-supported kit preparation

Fager

Calzavara

Sgarbossa

2019

Int J Adv Manuf Technol

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Kittingmeaning to supply assembly with components in presorted kitsis widely seen as beneficial for assembly quality and efficiency when there is a multitude of component variants. However, the process by which kits are preparedthe kit preparation is labour-intensive, and kit errors are problematic at assembly processes. The use of robotics to support kit preparation has received some attention by researchers, but literature is lacking with respect to how collaborative robotscobotscan support kit preparation activities. The purpose of this paper is to identify the potential of a cobot to support time-efficient batch preparation of kits. To address the purpose, the paper presents a mathematical model for estimation of the cycle time associated with cobotsupported kit preparation. The model is applied in a numerical example with experimental data from laboratory experiments, and cobot-supported kit preparation is compared with manual kit preparation. The findings suggest that cobot-supported kit preparation is beneficial with diverse kits and smaller components quantities per SKU (Stock Keeping Unit) and provides less variability of the outcome, when compared to manual kit preparation. The paper reveals several insights about cobotsupported kit preparation that can be valuable for both academics and practitioners. The model developed can be used by practitioners to assess the potential of cobots to support kit-batch preparation in association with assembly, spare parts, repair and maintenance, or business to business industry.

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Gesture-based human-robot interaction for human assistance in manufacturing

Cited by 118 publications

References 33 publications

Human-Robot Perception in Industrial Environments: A Survey

Human-Robot Perception in Industrial Environments: A Survey

Sustainable Move towards Flexible, Robotic, Human-Involving Workplace

Modelling time efficiency of cobot-supported kit preparation

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