Simultaneous Estimation of Material Properties and Pose for Deformable Objects from Depth and Color Images

In this paper we consider the problem of estimating 6D pose, material properties and deformation of an object grasped by a robot gripper. To estimate the parameters we minimize an error function incorporating visual and physical correctness. Through simulated and real-world experiments we demonstrate that we are able to find realistic 6D poses and elasticity parameters like Young’s modulus. This makes it possible to perform subsequent manipulation tasks, where accurate modelling of the elastic behaviour is important.

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