EDBT 2026 Demo / reviewers in the wild / expert
Amar Kamat
dblp:291/3882 · also Amar M. Kamat
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-1622-9067ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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 |
Robot manipulation · 62% Motion planning and robot control · 38% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation
grasping |
0.6 | 1 | 2022 | Source-Seeking Control of Unicycle Robots With 3-D-Printed Flexible Piezoresistive Sensors · IEEE Trans. Robotics 2022 |
Robotics › Motion planning and robot control › robot control › optimization-based control
gradient-based control |
0.2 | 1 | 2022 | Source-Seeking Control of Unicycle Robots With 3-D-Printed Flexible Piezoresistive Sensors · IEEE Trans. Robotics 2022 |
Robotics › Motion planning and robot control
mobile robot control |
0.2 | 1 | 2022 | Source-Seeking Control of Unicycle Robots With 3-D-Printed Flexible Piezoresistive Sensors · IEEE Trans. Robotics 2022 |
Methods — techniques the papers use, named apart from their topics
projected gradient ascent · 0.6extremum seeking control · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Source-Seeking Control of Unicycle Robots With 3-D-Printed Flexible Piezoresistive SensorsabstractIn this article, we present the design and experimental validation of source-seeking control algorithms for a unicycle mobile robot that is equipped with novel 3-D-printed flexible graphene-based piezoresistive airflow sensors. Based solely on a local gradient measurement from the airflow sensors, we propose and analyze a projected gradient ascent algorithm to solve the source-seeking problem. In the case of partial sensor failure, we propose a combination of extremum-seeking control with our projected gradient ascent algorithm. For both control laws, we prove the asymptotic convergence of the robot to the source. Numerical simulations were performed to validate the algorithms, and experimental validations are presented to demonstrate the efficacy of the proposed methods. Bayu Jayawardhana, Amar Kamat, Ajay Giri Prakash Kottapalli |
IEEE Trans. Robotics | 3 |