Cooperation of human and machines in assembly lines

Krüger, Jörg; Lien, Terje K.; Verl, Alexander

doi:10.1016/j.cirp.2009.09.009

Cited by 692 publications

(339 citation statements)

References 49 publications

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“…The study defines the levels of human-robot collaboration according to the cell complexity, to drive the probabilities of successful implementation. But as in the previously cited survey [2], the paper exposes the absence of high level human-robot collaboration, apart from "Intelligent Lift Assistants".…”

Section: Research On Human-machine Cooperation In the Industrymentioning

confidence: 96%

“…• In contrast with most existing human-machine manufacturing applications, where collision avoidance is guaranteed by a minimum security distance [2], our framework successfully manages direct physical contact between robot and human, and between robot and environment.…”

Section: Introductionmentioning

confidence: 99%

“…This is a key issue, since according to statistics of the Occupational Safety and Health Department of the US Department of Labour 1 , more than 30% of European manufacturing workers are affected by lower back pain, leading to enormous social and economic costs. A thorough state-of-theart on human-machine cooperation in manufacturing lines is provided in [2]. At the time of that survey (2009), the only hybrid assembly systems in manufacturing processes were weight compensators/balancers.…”

Section: Introductionmentioning

confidence: 99%

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Collaborative manufacturing with physical human–robot interaction

Cherubini¹,

Passama²,

Crosnier³

et al. 2016

Robotics and Computer-Integrated Manufacturing

479

188

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Although the concept of industrial cobots dates back to 1999, most present day hybrid human-machine assembly systems are merely weight compensators. Here, we present results on the development of a collaborative human-robot manufacturing cell for homokinetic joint assembly. The robot alternates active and passive behaviours during assembly, to lighten the burden on the operator in the first case, and to comply to his/her needs in the latter. Our approach can successfully manage direct physical contact between robot and human, and between robot and environment. Furthermore, it can be applied to standard position (and not torque) controlled robots, common in the industry. The approach is validated in a series of assembly experiments. The human workload is reduced, diminishing the risk of strain injuries. Besides, a complete risk analysis indicates that the proposed setup is compatible with the safety standards, and could be certified.

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Section: Research On Human-machine Cooperation In the Industrymentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Collaborative manufacturing with physical human–robot interaction

Cherubini¹,

Passama²,

Crosnier³

et al. 2016

Robotics and Computer-Integrated Manufacturing

479

188

View full text Add to dashboard Cite

show abstract

“…workplace sharing or workplace and time sharing systems [10]. A single ToF sensor is installed to monitor a peg-in-hole process environment where a KUKA robot is working and a human worker or any static object may act as obstacle.…”

Section: Twofold Strategy To Avoid Collisionsmentioning

confidence: 99%

“…A 3D-MLI sensor [10] installed on the table captures the depth information from the scene and localizes different object in the 3D working environment. While knowing different items like work-points, initial planned trajectory, the scene information in the presence and absence of obstacle, the R2P algorithm detailed in the program code below, calculates the safe robot trajectory.…”

Section: Robot Path Planning (R2p) Algorithmmentioning

confidence: 99%

Human-Robot Collaboration: Twofold Strategy Algorithm to Avoid Collisions Using ToF Sensor

Plapper¹

2015

IJMMM

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Abstract-The importance of Human Robot Interaction to complement human skills in a manufacturing environment with industrial robots increases the concerns over safety of human and the robot. It is necessary to identify collision risks and avoid them otherwise production stops may cost a huge amount to the industry. A robot working at manufacturing facility should be able to predict potential collisions and must be able to prevent i.e. react automatically for safe detour around obstacle/human. Currently, industrial robots are able to detect collisions after a real contact but the existing proposals for avoiding collisions are either computationally expensive or not very well adapted to human safety. The objective of this paper is to provide intelligence to the industrial robot to predict collision risks and react automatically without stopping the production in a static environment. The proposed approach using Time of Flight (TOF) camera, provides decision regarding trajectory correction and improvement by shifting robot to a secure position. The application presented in this paper is for safe KUKA robot trajectory generation in peg-in-hole assembly process in the laboratory context. Index Terms-Robot path planning, safe robot trajectory generation, collision detection and avoidance, vision based system, time of flight (ToF) sensor.

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