Safer hybrid workspace using human-robot interaction while sharing production activities

Meziane, Ramy; Li, Ping; Otis, Martin J.‐D.; Ezzaidi, Hassan; Cardou, Philippe

doi:10.1109/rose.2014.6952980

Cited by 19 publications

(16 citation statements)

References 23 publications

(23 reference statements)

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“…Since some applications could be found in a robotic control field, we will focus on the Human-Robot interaction model as shown in [33][34][35] and on the interesting problematic of finite-time stability frontier under critical values of impedance like damping and mass parameters, especially in the case where the states of the system are subject to disturbance.…”

Section: Discussionmentioning

confidence: 99%

Finite-Time Stabilization of Homogeneous Non-Lipschitz Systems

Khelil¹,

Otis²

2016

Preprint

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This paper focuses on the problem of finite-time stabilization of homogeneous, non-Lipschitz systems with dilations. A key contribution of this paper is the design of a virtual recursive Hölder, non-Lipschitz state feedback, which renders the non-Lipschitz systems in the special case dominated by a lower-triangular nonlinear system finite-time stable. The proof is based on a recursive design algorithm developed recently to construct the virtual Hölder continuous, finite-time stabilizer as well as a C 1 positive definite and proper Lyapunov function that guarantees finite-time stability of the non-Lipschitz nonlinear systems.

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Section: Discussionmentioning

confidence: 99%

Finite-Time Stabilization of Homogeneous Non-Lipschitz Systems

Khelil¹,

Otis²

2016

Preprint

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“…In this study, based on observation of Alexander et al [ 8 ], the following commands with mapping gestures are presented in Table 4 . Additional gestures with different commands could be certainly defined, as described in the introduction such as physical collaboration [ 10 ], autonomous action in shared activities [ 11 ], remote control motion [ 12 ], and learning new tasks [ 4 ].…”

Section: Methodsmentioning

confidence: 99%

“…This project suggests implementing cobot operating mode selection using the foot in the scheduling of production activities to improve manufacturing flexibility. Therefore, an operator could need, utilizing foot gestures, to communicate actions, to be executed by the cobot, and to select different operating modes such as physical collaboration [ 10 ], autonomous action in shared activities [ 11 ], remote control motion [ 12 ], and learning new tasks [ 4 ]. This process allows controlling possible modalities of high-dimensionality cobot with a low-dimensionality wearable device such as a smart armband or smart insole.…”

Section: Introductionmentioning

confidence: 99%

Image Generation for 2D-CNN Using Time-Series Signal Features from Foot Gesture Applied to Select Cobot Operating Mode

Aswad

Djogdom

Otis

et al. 2021

Sensors

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Advances in robotics are part of reducing the burden associated with manufacturing tasks in workers. For example, the cobot could be used as a “third-arm” during the assembling task. Thus, the necessity of designing new intuitive control modalities arises. This paper presents a foot gesture approach centered on robot control constraints to switch between four operating modalities. This control scheme is based on raw data acquired by an instrumented insole located at a human’s foot. It is composed of an inertial measurement unit (IMU) and four force sensors. Firstly, a gesture dictionary was proposed and, from data acquired, a set of 78 features was computed with a statistical approach, and later reduced to 3 via variance analysis ANOVA. Then, the time series collected data were converted into a 2D image and provided as an input for a 2D convolutional neural network (CNN) for the recognition of foot gestures. Every gesture was assimilated to a predefined cobot operating mode. The offline recognition rate appears to be highly dependent on the features to be considered and their spatial representation in 2D image. We achieve a higher recognition rate for a specific representation of features by sets of triangular and rectangular forms. These results were encouraging in the use of CNN to recognize foot gestures, which then will be associated with a command to control an industrial robot.

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“…The workstation consists of the Flexible Manufacturing System (FMS) used by Meziane et al [ 52 ]. It includes a robot with human interaction skills and a Programmable Logic Controller (PLC) connected to the robot, as well as other components such as a conveyor, a distributor and a storage system.…”

Section: Methodsmentioning

confidence: 99%

Wearable Devices for Classification of Inadequate Posture at Work Using Neural Networks

Barkallah

Freulard

Otis

et al. 2017

Sensors

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Inadequate postures adopted by an operator at work are among the most important risk factors in Work-related Musculoskeletal Disorders (WMSDs). Although several studies have focused on inadequate posture, there is limited information on its identification in a work context. The aim of this study is to automatically differentiate between adequate and inadequate postures using two wearable devices (helmet and instrumented insole) with an inertial measurement unit (IMU) and force sensors. From the force sensors located inside the insole, the center of pressure (COP) is computed since it is considered an important parameter in the analysis of posture. In a first step, a set of 60 features is computed with a direct approach, and later reduced to eight via a hybrid feature selection. A neural network is then employed to classify the current posture of a worker, yielding a recognition rate of 90%. In a second step, an innovative graphic approach is proposed to extract three additional features for the classification. This approach represents the main contribution of this study. Combining both approaches improves the recognition rate to 95%. Our results suggest that neural network could be applied successfully for the classification of adequate and inadequate posture.

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Safer hybrid workspace using human-robot interaction while sharing production activities

Cited by 19 publications

References 23 publications

Finite-Time Stabilization of Homogeneous Non-Lipschitz Systems

Finite-Time Stabilization of Homogeneous Non-Lipschitz Systems

Image Generation for 2D-CNN Using Time-Series Signal Features from Foot Gesture Applied to Select Cobot Operating Mode

Wearable Devices for Classification of Inadequate Posture at Work Using Neural Networks

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