1 research outputs found
In-Hand Object-Dynamics Inference using Tactile Fingertips
Having the ability to estimate an object's properties through interaction
will enable robots to manipulate novel objects. Object's dynamics, specifically
the friction and inertial parameters have only been estimated in a lab
environment with precise and often external sensing. Could we infer an object's
dynamics in the wild with only the robot's sensors? In this paper, we explore
the estimation of dynamics of a grasped object in motion, with tactile force
sensing at multiple fingertips. Our estimation approach does not rely on torque
sensing to estimate the dynamics. To estimate friction, we develop a control
scheme to actively interact with the object until slip is detected. To robustly
perform the inertial estimation, we setup a factor graph that fuses all our
sensor measurements on physically consistent manifolds and perform inference.
We show that tactile fingertips enable in-hand dynamics estimation of low mass
objects.Comment: Accepted at IEEE Transactions on Robotics (T-RO). Website:
https://sites.google.com/view/tactile-obj-dynamic