Assessment of physical exposure to musculoskeletal risks in collaborative robotics using dynamic simulation

Many industrial tasks cannot be executed by a robot alone. A way to help workers in order to decrease the risk of musculoskeletal disorders is to assist them with a collaborative robot. Yet assessing its usefulness to the worker remains costly because it usually requires a prototype. We propose a dynamic simulation framework to model the performing of a task jointly by a virtual manikin and a robot. It allows to measure physical quantities in order to perform an ergonomic assessment of the robot. Experiments are carried out on two different robots. The results show that the proposed simulation framework is helpful for designing collaborative robots. Further work includes enhancing the simulation realism and validation on a real robot

Automatic selection of ergonomic indicators for the design of collaborative robots: a virtual-human in the loop approach

Conference of 2014 14th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2014 ; Conference Date: 18 November 2014 Through 20 November 2014; Conference Code:112990International audienceThe growing number of musculoskeletal disorders in industry could be addressed by the use of collaborative robots, which allow the joint manipulation of objects by both a robot and a person. Designing these robots requires to assess the ergonomic benefit they offer. However there is a lack of adapted assessment methods in the literature. Many biomechanical quantities can represent the physical solicitations to which the worker is exposed, but their relevance strongly depends on the considered task. This paper presents a method to automatically select relevant ergonomic indicators for a given task to be performed with a collaborative robot. A virtual human simulation is used to estimate thirty indicators for varying human and robot features. A variance-based analysis is then conducted to extract the most discriminating indicators. The method is validated on several different tasks. The relevance of the proposed approach is confirmed by the obtained results

Rhodococcus equi's Extreme Resistance to Hydrogen Peroxide Is Mainly Conferred by One of Its Four Catalase Genes

Rhodococcus equi is one of the most widespread causes of disease in foals aged from 1 to 6 months. R. equi possesses antioxidant defense mechanisms to protect it from reactive oxygen metabolites such as hydrogen peroxide (H(2)O(2)) generated during the respiratory burst of phagocytic cells. These defense mechanisms include enzymes such as catalase, which detoxify hydrogen peroxide. Recently, an analysis of the R. equi 103 genome sequence revealed the presence of four potential catalase genes. We first constructed \u394katA-, \u394katB-, \u394katC-and \u394katD-deficient mutants to study the ability of R. equi to survive exposure to H(2)O(2)in vitro and within mouse peritoneal macrophages. Results showed that \u394katA and, to a lesser extent \u394katC, were affected by 80 mM H(2)O(2). Moreover, katA deletion seems to significantly affect the ability of R. equi to survive within murine macrophages. We finally investigated the expression of the four catalases in response to H(2)O(2) assays with a real time PCR technique. Results showed that katA is overexpressed 367.9 times (\ub1122.6) in response to exposure to 50 mM of H(2)O(2) added in the stationary phase, and 3.11 times (\ub10.59) when treatment was administered in the exponential phase. In untreated bacteria, katB, katC and katD were overexpressed from 4.3 to 17.5 times in the stationary compared to the exponential phase. Taken together, our results show that KatA is the major catalase involved in the extreme H(2)O(2) resistance capability of R. equi

Experimental assessment of the quality of ergonomic indicators for dynamic systems computed using a digital human model

International audienceThe growing number of musculoskeletal disorders in industry could be addressed by the use of collaborative robots, which allow the joint manipulation of objects by both a robot and a person. Designing these robots requires to assess the ergonomic benefit they offer. Current methods use a posteriori assessment, i.e. observation of a worker performing the task, and require a physical mock-up of the robot. Moreover, they exclude dynamic phenomena because their measurements require heavy instrumentation. However, collaborative robots are not static objects, but dynamic systems which motion influences and is influenced by the physical interaction with the worker. Plus, the worker him/herself is also a dynamic system, on which dynamic phenomena have ergonomic consequences, even without the presence of a collaborative robot. In order to perform more thorough assessments of the ergonomic performances of dynamic systems, it is proposed to use a dynamic digital human model (DHM) for the evaluation, associated with a dedicated ergonomic metric. This paper presents preliminary results on three ergonomic indicators formulated to meet the requirements of ergonomic evaluations of dynamic systems. They evaluate respectively the position of the worker, his physical effort and the energy spent during the task. The same manual task is performed by seven human subjects under different time, load and geometric constraints. Each performance is recorded and replayed with a dynamic DHM in a dynamic simulation framework, in order to calculate the values of the indicators. All three indicators are strongly affected by the geometric parameters in a way that is consistent with ergonomic guidelines. Besides, a linear correlation between the values of the indicators and the strenuousness perceived by the subjects is observed. Moreover, the results show that the relevance of an indicator is strongly affected by the task features, especially its duration. Future work will be directed towards automatic selection of relevant indicators for a given task

Dépistage des cancers de la cavité buccale (étude de l'expression des membres de la famille p53 et des mutations du gène TP53)

CAEN-BU Médecine pharmacie (141182102) / SudocSudocFranceF

Les cancers ORL (épidémiologie, traitements, dépistage et prévention)

CAEN-BU Médecine pharmacie (141182102) / SudocLYON1-BU Santé (693882101) / SudocSudocFranceF

Virtual ergonomics for the design of collaborative robots

International audienc

A digital human tool for guiding the ergonomic design of collaborative robots

International audienceThe growing number of musculoskeletal disorders in industry could be addressed by the use of collaborative robots, which allow the joint manipulation of objects by both a robot and a person. Efficiently designing these robots requires to assess the ergonomic benefit they offer. Despite the advances in human biomechanics and digital human model (DHM) simulation tools, the existing software for ergonomic analyses remain ill-adapted for collaborative robots design, because of both the DHM animation techniques and the biomechanic criteria that are measured. This paper presents a generic tool for performing detailed ergonomic assessments of activities including collaborative robots. The proposed method relies on an evaluation carried out within a digital world, using a DHM to simulate the worker. The evaluation of the robot-worker system can thus easily be performed throughout the whole design process. Multiple ergonomic indicators are defined in order to exhaustively estimate the different biomechanical demands which occur during manual activities. In order to simplify their interpretation, a sensitivity analysis is conducted to extract relevant indicators which best summarize the overall ergonomic performance of the considered activity, as well as identify the robot parameters which mainly affect this performance. In this purpose, multiple virtual human simulations of the activity-in which the DHM interacting with the collaborative robot is animated with an optimization-based whole-body controller-are run to measure all the ergonomic indicators for varying human and robot features. The relevant indicators resulting from this analysis can then be used to easily compare different robots, or to automatically optimize certain design parameters of a robot. The whole method is applied to the optimization of a robot morphology for assisting a drilling gesture. The sensitivity analysis is performed on 28 ergonomic indicators with 8 different human and robot parameters, resulting in a total of 8000 simulations. This analysis enables to reduce the number of ergonomic indicators to consider in the optimization from 28 to only 3, hence facilitating the convergence of the optimization: robots performing well on all 3 ergonomic objectives are produced with an evolutionary algorithm in about 150 generations. The comparison of the situations without assistance and with near-optimal robots shows some lack of transparency in the robots, but a comparatively significant improvements in the force-related ergonomic indicators. This result demonstrates the benefit of the optimized robots and thereby confirms the relevance of the proposed approach to provide robot designers with interesting preliminary designs to be further worked on

Assessing and improving human movements using sensitivity analysis and digital human simulation

International audienceEnhancing the performance of technical movements aims both at improving operational results and at reducing biomechanical demands. Advances in human biomechanics and modeling tools allow to evaluate human performance with more and more details. Finding the right modifications to improve the performance is, however, still addressed with extensive time consuming trial-and-error processes. This paper presents a framework for easily assessing human movements and automatically providing recommendations to improve their performances. An optimization-based whole-body controller is used to dynamically replay human movements from motion capture data, to evaluate existing movements. Automatic digital human simulations are then run to estimate performance indicators when the movement is performed in many different ways. Sensitivity indices are thereby computed to quantify the influence of postural parameters on the performance. Based on the results of the sensitivity analysis, recommendations for posture improvement are provided. The method is successfully validated on a drilling activity

Human-oriented design of collaborative robots

International audienceCollaborative robotics is a possible solution to the problem of musculoskeletal disorders (MSDs) in industry, but efficiently designing such robots remains an issue because ergonomic assessment tools are ill-adapted to such devices. This paper presents a generic method for performing detailed ergonomic assessments of co-manipulation activities and its application to the optimal design of collaborative robots. Multiple ergonomic indicators are defined to estimate the different biomechanical demands which occur during manual activities. For any given activity, these indicators are measured through dynamic virtual human simulations, for varying human and robot features. Sensitivity indices are thereby computed to quantify the influence of each parameter of the robot and identify those which should mainly be modified to enhance the ergonomic performance. The sensitivity analysis also allows to extract the indicators which best summarize the overall ergonomic performance of the activity. An evolutionary algorithm is then used to optimize the influential parameters of the robot with respect to the most informative ergonomic indicators, in order to generate an efficient robot design. The whole method is applied to the optimization of a robot morphology for assisting a drilling activity. The performances of the resulting robots confirm the relevance of the proposed approach