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A General Visual-Impedance Framework for Effectively Combining Vision and Force Sensing in Feature Space
Abstract : Robotic systems are increasingly used to work in dynamic and/or unstructured environments and to operate with a high degree of safety and autonomy. Consequently, they are often equipped with external sensors capable of perceiving the environment (e.g. cameras) and the contacts that may arise (e.g. force/torque sensors). This paper proposes a general framework for combining force and visual information in the visual feature space. By leveraging recent results on the derivation of visual servo dynamics, we generalize the treatment regardless of the visual features chosen. Vision and force sensing are coupled in the feature space, avoiding both the convergence to a local minimum and the arising of inconsistencies at the actuation level. Any task space direction is simultaneously controlled by both vision and force. Compliance against interaction forces is achieved in feature space along the features defining the visual task. Experiments on a real platform are carried out to evaluate the effectiveness of the proposed framework.
https://hal.inria.fr/hal-03180717
Contributor : Eric Marchand <>
Submitted on : Thursday, March 25, 2021 - 11:14:05 AM
Last modification on : Wednesday, April 14, 2021 - 1:54:08 PM
Contributor : Eric Marchand <>
Submitted on : Thursday, March 25, 2021 - 11:14:05 AM
Last modification on : Wednesday, April 14, 2021 - 1:54:08 PM
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2021_ral_oliva.pdf
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