Explore, Approach, and Terminate - Evaluating Subtasks in Active Visual Object Search Based on Deep Reinforcement Learning

Jan Fabian Schmid
Jan Fabian Schmid

IROS, pp. 5008-5013, 2019.

Cited by: 0|Views10
EI

Abstract:

Searching for objects and distinguishing task-relevant objects from others is a key requirement for service robots. We propose a reinforcement learning solution to the active visual object search problem. Our method successfully learns to explore the environment, to approach the target object, and to decide when to terminate the search as...More

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