We consider the problem of automating the motion performed by a human operator when manipulating a specimen in tasks such as visual inspections for defects. This is a typical situation in which the trajectory of the manipulated object is hardly described by analytical functions, since the actual movements are suggested more by the operator's experience, rather than a standardized protocol. In principle, traditional motion capture systems based on computer vision methods could be employed to reconstruct the motion: however, especially when manipulating small specimens, visual occlusions caused by the operator's hand prevent the correct tracking of the moving object. In this paper, we investigate the possibility of reconstructing the motion by using the information provided by a low-cost MEMS Inertial Measurement Unit (IMU) attached to the specimen. For simple manipulating tasks such as shaking and rotations, we show that the motion capture system based on inertial measurements can be effectively used. © 2011 IEEE.
Motion reconstruction with a low-cost MEMS IMU for the automation of human operated specimen manipulation
Antonello R.;Oboe R.
2011
Abstract
We consider the problem of automating the motion performed by a human operator when manipulating a specimen in tasks such as visual inspections for defects. This is a typical situation in which the trajectory of the manipulated object is hardly described by analytical functions, since the actual movements are suggested more by the operator's experience, rather than a standardized protocol. In principle, traditional motion capture systems based on computer vision methods could be employed to reconstruct the motion: however, especially when manipulating small specimens, visual occlusions caused by the operator's hand prevent the correct tracking of the moving object. In this paper, we investigate the possibility of reconstructing the motion by using the information provided by a low-cost MEMS Inertial Measurement Unit (IMU) attached to the specimen. For simple manipulating tasks such as shaking and rotations, we show that the motion capture system based on inertial measurements can be effectively used. © 2011 IEEE.Pubblicazioni consigliate
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