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Quantum Deep Reinforcement Learning for Robot Navigation Tasks
In this work, we utilize Quantum Deep Reinforcement Learning as method to learn navigation tasks for a simple, wheeled robot in three simulated environments of increasing complexity.
A Development Cycle for Automated Self-Exploration of Robot Behaviors
In this paper we introduce Q-Rock, a development cycle for the automated self-exploration and qualification of robot behaviors.
Combinatorics of a Discrete Trajectory Space for Robot Motion Planning
Motion planning is a difficult problem in robot control.
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