Quantum Robot: Structure, Algorithms and Applications
Abstract
A kind of brand-new robot, quantum robot, is proposed through fusing quantum theory with robot technology. Quantum robot is essentially a complex quantum system and it is generally composed of three fundamental parts: MQCU (multi quantum computing units), quantum controller/actuator, and information acquisition units. Corresponding to the system structure, several learning control algorithms including quantum searching algorithm and quantum reinforcement learning are presented for quantum robot. The theoretic results show that quantum robot can reduce the complexity of O(N^2) in traditional robot to O(N^(3/2)) using quantum searching algorithm, and the simulation results demonstrate that quantum robot is also superior to traditional robot in efficient learning by novel quantum reinforcement learning algorithm. Considering the advantages of quantum robot, its some potential important applications are also analyzed and prospected.
Cite
@article{arxiv.quant-ph/0506155,
title = {Quantum Robot: Structure, Algorithms and Applications},
author = {Dao-Yi Dong and Chun-Lin Chen and Chen-Bin Zhang and Zong-Hai Chen},
journal= {arXiv preprint arXiv:quant-ph/0506155},
year = {2007}
}
Comments
19 pages, 4 figures, 2 tables