Path Planning and Design for AFM based Nano-manipulation using Probability Distribution

Shuai Yuan; Lianqing Liu; Zhidong Wang; Jingyi Xing; Ning Xi; Yuechao Wang

doi:10.1109/cbs.2017.8266095

Path Planning and Design for AFM based Nano-manipulation using Probability Distribution

Shuai Yuan^*, Lianqing Liu, Zhidong Wang, Jingyi Xing, Ning Xi, Yuechao Wang

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

1 Citation (Scopus)

Abstract

In AFM nanomanipulation, the uncertainty of tip position in the task space can lead to inefficient nanomanipulation. To resolve this problem, the paper proposes a method which uses the local scan to obtain the observation distance. Then the landmark adjacency matrix is established for designing the observed landmarks. Next, colony optimization and Dijkstra's Algorithm are used to plan the tip trajectory, which reduces the cost greatly. Finally, the experiment results illustrate that the proposed algorithm can perform effective nano-manipulation.

Original language	English
Title of host publication	2017 IEEE International Conference on Cyborg and Bionic Systems (CBS)
Publisher	IEEE
Pages	188-193
ISBN (Electronic)	978-1-5386-3194-2
DOIs	https://doi.org/10.1109/cbs.2017.8266095
Publication status	Published - Oct 2017
Event	2017 IEEE International Conference on Cyborg and Bionic Systems (CBS 2017) - Beijing, China Duration: 17 Oct 2017 → 19 Oct 2017

Conference

Conference	2017 IEEE International Conference on Cyborg and Bionic Systems (CBS 2017)
Place	China
City	Beijing
Period	17/10/17 → 19/10/17

Research Keywords

AFM Trajectory planning
Nanomanipulation
ant colony optimization
Dijkstra's Algorithm
NANOMANIPULATIONS
LOCALIZATION

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10.1109/cbs.2017.8266095

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@inproceedings{223f03b79fbc4d138813ec7114e7123b,

title = "Path Planning and Design for AFM based Nano-manipulation using Probability Distribution",

abstract = "In AFM nanomanipulation, the uncertainty of tip position in the task space can lead to inefficient nanomanipulation. To resolve this problem, the paper proposes a method which uses the local scan to obtain the observation distance. Then the landmark adjacency matrix is established for designing the observed landmarks. Next, colony optimization and Dijkstra's Algorithm are used to plan the tip trajectory, which reduces the cost greatly. Finally, the experiment results illustrate that the proposed algorithm can perform effective nano-manipulation.",

keywords = "AFM Trajectory planning, Nanomanipulation, ant colony optimization, Dijkstra's Algorithm, NANOMANIPULATIONS, LOCALIZATION",

author = "Shuai Yuan and Lianqing Liu and Zhidong Wang and Jingyi Xing and Ning Xi and Yuechao Wang",

year = "2017",

month = oct,

doi = "10.1109/cbs.2017.8266095",

language = "English",

pages = "188--193",

booktitle = "2017 IEEE International Conference on Cyborg and Bionic Systems (CBS)",

publisher = "IEEE",

address = "United States",

note = "2017 IEEE International Conference on Cyborg and Bionic Systems (CBS 2017) ; Conference date: 17-10-2017 Through 19-10-2017",

}

Yuan, S, Liu, L, Wang, Z, Xing, J, Xi, N & Wang, Y 2017, Path Planning and Design for AFM based Nano-manipulation using Probability Distribution. in 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS). IEEE, pp. 188-193, 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS 2017), Beijing, China, 17/10/17. https://doi.org/10.1109/cbs.2017.8266095

Path Planning and Design for AFM based Nano-manipulation using Probability Distribution. / Yuan, Shuai; Liu, Lianqing; Wang, Zhidong et al.
2017 IEEE International Conference on Cyborg and Bionic Systems (CBS). IEEE, 2017. p. 188-193.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Path Planning and Design for AFM based Nano-manipulation using Probability Distribution

AU - Yuan, Shuai

AU - Liu, Lianqing

AU - Wang, Zhidong

AU - Xing, Jingyi

AU - Xi, Ning

AU - Wang, Yuechao

PY - 2017/10

Y1 - 2017/10

N2 - In AFM nanomanipulation, the uncertainty of tip position in the task space can lead to inefficient nanomanipulation. To resolve this problem, the paper proposes a method which uses the local scan to obtain the observation distance. Then the landmark adjacency matrix is established for designing the observed landmarks. Next, colony optimization and Dijkstra's Algorithm are used to plan the tip trajectory, which reduces the cost greatly. Finally, the experiment results illustrate that the proposed algorithm can perform effective nano-manipulation.

AB - In AFM nanomanipulation, the uncertainty of tip position in the task space can lead to inefficient nanomanipulation. To resolve this problem, the paper proposes a method which uses the local scan to obtain the observation distance. Then the landmark adjacency matrix is established for designing the observed landmarks. Next, colony optimization and Dijkstra's Algorithm are used to plan the tip trajectory, which reduces the cost greatly. Finally, the experiment results illustrate that the proposed algorithm can perform effective nano-manipulation.

KW - AFM Trajectory planning

KW - Nanomanipulation

KW - ant colony optimization

KW - Dijkstra's Algorithm

KW - NANOMANIPULATIONS

KW - LOCALIZATION

UR - http://www.scopus.com/inward/record.url?scp=85050512015&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85050512015&origin=recordpage

U2 - 10.1109/cbs.2017.8266095

DO - 10.1109/cbs.2017.8266095

M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 188

EP - 193

BT - 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS)

PB - IEEE

T2 - 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS 2017)

Y2 - 17 October 2017 through 19 October 2017

ER -

Path Planning and Design for AFM based Nano-manipulation using Probability Distribution

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