Demo Data from EDBT 2026 / reviewers in the wild / expert
Komal Vendidandi
dblp:266/3211
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021
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 |
Motion planning and robot control · 54% Robot manipulation · 46% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
assembly |
0.7 | 1 | 2023 | Auto-Assembly: a framework for automated robotic assembly directly from CAD · ICRA 2023 |
Robotics › Robot manipulation › assembly
automated assembly |
0.7 | 1 | 2023 | Auto-Assembly: a framework for automated robotic assembly directly from CAD · ICRA 2023 |
Robotics › Motion planning and robot control
motion planning |
0.7 | 1 | 2023 | Auto-Assembly: a framework for automated robotic assembly directly from CAD · ICRA 2023 |
Robotics › Motion planning and robot control
path planning |
0.7 | 1 | 2023 | Auto-Assembly: a framework for automated robotic assembly directly from CAD · ICRA 2023 |
Robotics › Motion planning and robot control › assembly planning
assembly sequence generation |
0.2 | 1 | 2023 | Auto-Assembly: a framework for automated robotic assembly directly from CAD · ICRA 2023 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.7CAD-based planning · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Auto-Assembly: a framework for automated robotic assembly directly from CADabstractIn this work, we propose a framework called Auto-Assembly for automated robotic assembly from design files and demonstrate a practical implementation on modular parts joined by fastening using a robotic cell consisting of two robots. We show the flexibility of the approach by testing it on different input designs. Auto-Assembly consists of several parts: design analysis, assembly sequence generation, bill-of-process (BOP) generation, conversion of the BOP to control code, path planning, simulation, and execution of the control code to assemble parts in the physical environment. Fedor Chervinskii, Sergei Zobov, Aleksandr Rybnikov, Danil Petrov, Komal Vendidandi |
ICRA | 5 |