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Incremental Distributed Inference from Arbitrary Poses and Unknown Data Association: Using Collaborating Robots to Establish a Common Reference

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PROJECT TITLE :

Incremental Distributed Inference from Arbitrary Poses and Unknown Data Association: Using Collaborating Robots to Establish a Common Reference

ABSTRACT:

High-accuracy localization could be a basic capability that is essential for autonomous reliable operation in varied applications, including autonomous driving, monitoring of an environmental phenomena, mapping, and tracking. The problem can be formulated as inference over the robot's state and probably additional variables of interest based mostly on incoming sensor measurements and a priori data, if such data exists. Moreover, in varied applications, this inference problem must be solved in real time, so requiring computationally efficient inference methods.


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Incremental Distributed Inference from Arbitrary Poses and Unknown Data Association: Using Collaborating Robots to Establish a Common Reference - 4.7 out of 5 based on 68 votes

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