Mobile robots are increasingly utilised in automated plants to the purpose of moving wares and material between the different production lines and logistic areas. In this context, the presence of human operators in the facility is frequently allowed to carry out or supervise some phases of the production. The problem arises of how to make the co-existence possible with controlled risks for the operator and without affecting the productivity with frequent interruptions. In this paper we propose a solution to this problem based on a probabilistic technique. A system of visual sensor (mounted on the mobile robots) detects the presence of a human operator and a discrete abstraction (essentially a discrete-time Markov chain) is used to predict his/her motion and hence find the probability of an accidental injury. For the computation of the latter, we combine the probability of having a collision with a given speed with the probability of receiving an injury out of the collision (taken from ...
A Probabilistic methodology for predicting injuries to human operators in automated production lines / Asaula, Ruslan; Fontanelli, Daniele; Palopoli, Luigi. - STAMPA. - (2009), pp. 1-8. ( 14th IEEE Conference on Emerging Technologies and Factory Automation Mallorca 22nd-25th September 2009) [10.1109/ETFA.2009.5347119].
A Probabilistic methodology for predicting injuries to human operators in automated production lines
Asaula, Ruslan;Fontanelli, Daniele;Palopoli, Luigi
2009-01-01
Abstract
Mobile robots are increasingly utilised in automated plants to the purpose of moving wares and material between the different production lines and logistic areas. In this context, the presence of human operators in the facility is frequently allowed to carry out or supervise some phases of the production. The problem arises of how to make the co-existence possible with controlled risks for the operator and without affecting the productivity with frequent interruptions. In this paper we propose a solution to this problem based on a probabilistic technique. A system of visual sensor (mounted on the mobile robots) detects the presence of a human operator and a discrete abstraction (essentially a discrete-time Markov chain) is used to predict his/her motion and hence find the probability of an accidental injury. For the computation of the latter, we combine the probability of having a collision with a given speed with the probability of receiving an injury out of the collision (taken from ...| File | Dimensione | Formato | |
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