dorsal/arxiv
View SchemaQuantum Robot: Structure, Algorithms and Applications
| Authors | Dao-Yi Dong, Chun-Lin Chen, Chen-Bin Zhang, Zong-Hai Chen |
|---|---|
| Categories | |
| ArXiv ID | quant-ph/0506155 |
| URL | https://arxiv.org/abs/quant-ph/0506155 |
| DOI | 10.1017/S0263574705002596 |
| Journal | Robotica 24(2006)513-521 |
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.
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"abstract": "A kind of brand-new robot, quantum robot, is proposed through fusing quantum\ntheory with robot technology. Quantum robot is essentially a complex quantum\nsystem and it is generally composed of three fundamental parts: MQCU (multi\nquantum computing units), quantum controller/actuator, and information\nacquisition units. Corresponding to the system structure, several learning\ncontrol algorithms including quantum searching algorithm and quantum\nreinforcement learning are presented for quantum robot. The theoretic results\nshow that quantum robot can reduce the complexity of O(N^2) in traditional\nrobot to O(N^(3/2)) using quantum searching algorithm, and the simulation\nresults demonstrate that quantum robot is also superior to traditional robot in\nefficient learning by novel quantum reinforcement learning algorithm.\nConsidering the advantages of quantum robot, its some potential important\napplications are also analyzed and prospected.",
"arxiv_id": "quant-ph/0506155",
"authors": [
"Dao-Yi Dong",
"Chun-Lin Chen",
"Chen-Bin Zhang",
"Zong-Hai Chen"
],
"categories": [
"quant-ph"
],
"doi": "10.1017/S0263574705002596",
"journal_ref": "Robotica 24(2006)513-521",
"title": "Quantum Robot: Structure, Algorithms and Applications",
"url": "https://arxiv.org/abs/quant-ph/0506155"
},
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