Simultaneous Tactile Estimation and Control for Extrinsic Dexterity
arxiv(2024)
摘要
We introduce a novel approach that combines tactile estimation and control
for in-hand object manipulation. By integrating measurements from robot
kinematics and an image-based tactile sensor, our framework estimates and
tracks object pose while simultaneously generating motion plans to control the
pose of a grasped object. This approach consists of a discrete pose estimator
that uses the Viterbi decoding algorithm to find the most likely sequence of
object poses in a coarsely discretized grid, and a continuous pose
estimator-controller to refine the pose estimate and accurately manipulate the
pose of the grasped object. Our method is tested on diverse objects and
configurations, achieving desired manipulation objectives and outperforming
single-shot methods in estimation accuracy. The proposed approach holds
potential for tasks requiring precise manipulation in scenarios where visual
perception is limited, laying the foundation for closed-loop behavior
applications such as assembly and tool use. Please see supplementary videos for
real-world demonstration at https://sites.google.com/view/texterity.
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