Demo Data from VLDB 2026 / reviewers in the wild / expert
Mathew Prokos
dblp:48/4492
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Robot manipulation · 77% Motion planning and robot control · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › micro/nano manipulation
nanomanipulation |
0.1 | 1 | 2005 | Planning and Control for Automated Nanorobotic Assembly · ICRA 2005 |
Robotics › Motion planning and robot control
trajectory planning |
0.0 | 1 | 2005 | Planning and Control for Automated Nanorobotic Assembly · ICRA 2005 |
Methods — techniques the papers use, named apart from their topics
local scanning · 0.1CAD-guided path planning · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Planning and Control for Automated Nanorobotic AssemblyabstractNanomanufacturing using Atomic Force Microcopy has been widely investigated. Most of nanomanipulation schemes go through the scan-design-manipulation-scan cycle manually which is time consuming and inefficient. Automated AFM tip path planning is desirable for nanomanufacturing, but does not receive much attention. In this paper, a CAD guided automated nanomanufacturing system is presented. Based on the CAD model of a nanostructure, the manipulation paths for both nanoparticles and nanorods are generated automatically. A local scanning method is developed to compensate for the random drift that may cause the failure of the nano-assembly. The experimental results demonstrate that the developed algorithm can be employed to manufacture nanostructures efficiently. The research work opens a door to the CAD guided automated nanomanufacturing. Heping Chen, Ning Xi 0001, Guangyong Li, Jiangbo Zhang, Mathew Prokos |
ICRA | 5 |