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.