Demo Data from EDBT 2026 / reviewers in the wild / expert
Alec Kanyuck
dblp:246/7876
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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 |
Motion planning and robot control · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › multi-robot control
multi-robot trajectory generation |
0.4 | 1 | 2019 | Generation of Synchronized Configuration Space Trajectories of Multi-Robot Systems · ICRA 2019 |
Robotics › Motion planning and robot control
trajectory optimization |
0.4 | 1 | 2019 | Generation of Synchronized Configuration Space Trajectories of Multi-Robot Systems · ICRA 2019 |
Robotics › Motion planning and robot control
trajectory planning |
0.4 | 1 | 2019 | Generation of Synchronized Configuration Space Trajectories of Multi-Robot Systems · ICRA 2019 |
Methods — techniques the papers use, named apart from their topics
successive refinement · 0.4nonlinear optimization · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Generation of Synchronized Configuration Space Trajectories of Multi-Robot SystemsabstractWe pose the problem of path-constrained trajectory generation for the synchronous motion of multi-robot systems as a non-linear optimization problem. Our method determines appropriate parametric representation for the configuration variables, generates an approximate solution as a starting point for the optimization method, and uses successive refinement techniques to solve the problem in a computationally efficient manner. We have demonstrated the effectiveness of the proposed method on challenging simulation and physical experiments with high degrees of freedom robotic systems. Ariyan M. Kabir, Alec Kanyuck, Rishi K. Malhan, Aniruddha V. Shembekar, Shantanu Thakar, Brual C. Shah, Satyandra K. Gupta |
ICRA | 2 |