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Mass Estimation of a Moving Object Through Minimal Manipulation Interaction

Sergio Aguilera, Muhammad Ali Murtaza, Ye Zhao, Seth Hutchinson

Year
2021
Citations
2

Abstract

In this paper, we study the problem of dynamic interaction between a robot and an unknown object (e.g., catching a ball, or handing off an object during locomotion). In particular, we propose a method for estimating the inertial parameters of an object during dynamic interaction, while minimally altering the trajectory of the object – a minimal interaction approach. Our method combines trajectory estimation (e.g., using standard methods from computer vision) with a model-based estimator that exploits the robot’s known dynamic model. We first develop the method for a generalized three-dimensional problem, and then evaluate the method for the case of an object moving along a linear trajectory. We present experimental results obtained using a KUKA iiwa 7 interacting with rolling balls of varying mass. Our experiments demonstrate that the mass of the objects can be accurately estimated at the moment of impact when accurate object trajectory estimates are available, and that significant improvement can be obtained by incorporating force measurements at the contact point while following the object.

Keywords

TrajectoryObject (grammar)EstimatorComputer scienceBall (mathematics)Computer visionRobotArtificial intelligenceMoment (physics)Inertial frame of reference

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