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Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera

Zhongkai Zhang, Antoine Petit, Jérémie Dequidt, Christian Duriez

Year
2019
Citations
18

Abstract

Benefiting from the deformability of soft robots, calibration, and force sensing for soft robots are possible using an external vision-based system, instead of embedded mechatronic force sensors. In this letter, we first propose a calibration method to calibrate both the sensor-robot coordinate system and the actuator inputs. This task is addressed through a sequential optimization problem for both variables. We also introduce an external force sensing system based on a real-time finite element (FE) model with the assumption of static configurations, and which consists of two steps: force location detection and force intensity computation. The algorithm that estimates force location relies on the segmentation of the point cloud acquired by an RGB-D camera. Then, the force intensities can be computed by solving an inverse quasi-static problem based on matching the FE model with the point cloud of the soft robot. As for validation, the proposed strategies for calibration and force sensing have been tested using a parallel soft robot driven by four cables.

Keywords

RobotCalibrationComputer scienceComputer visionArtificial intelligencePoint cloudRGB color modelRobot calibrationActuatorSimulation

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