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- W2034016056 abstract "We propose a method for handling persistent visual occlusions that disrupt visual tracking for eye-in-hand systems. Our approach allows a robot to “look behind” an occluder and re-acquire its target. To allow efficient planning, we avoid exhaustive mapping of the 3D occluder into configuration space, and instead use informed samples to strike a balance between target search and information gain. A particle filter continuously estimates the target location when it is not visible. Meanwhile, we build a simple but effective map of the occluder's extents to compute potential occlusion-clearing motions using very few calls to efficient approximations of inverse kinematics. Our mixed-initiative cost function balances the goal of directly locating the target with the goal of gaining information through mapping the occluder. Monte-Carlo optimization with efficient data-driven proposals allows us to approximate one-step solutions efficiently. Experimental evaluation performed on a realistic simulator shows that our method can quickly obtain clear views of the target, even when occlusions are persistent and significant camera motion is required." @default.
- W2034016056 created "2016-06-24" @default.
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- W2034016056 date "2013-05-01" @default.
- W2034016056 modified "2023-09-24" @default.
- W2034016056 title "Overcoming unknown occlusions in eye-in-hand visual search" @default.
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- W2034016056 doi "https://doi.org/10.1109/icra.2013.6631004" @default.
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