Demo Data from EDBT 2026 / reviewers in the wild / expert
Rutwik Kulkarni
dblp:249/4718
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computing education · 100% | |
| Artificial intelligence
1 paper |
Legged, aerial and field robots · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computing education
robotics education |
0.9 | 1 | 2025 | VizFlyt: Perception-centric Pedagogical Framework For Autonomous Aerial Robots · ICRA 2025 |
Robotics › Legged, aerial and field robots
aerial robots |
0.3 | 1 | 2025 | VizFlyt: Perception-centric Pedagogical Framework For Autonomous Aerial Robots · ICRA 2025 |
Robotics › Legged, aerial and field robots › aerial robots
autonomous flight |
0.3 | 1 | 2025 | VizFlyt: Perception-centric Pedagogical Framework For Autonomous Aerial Robots · ICRA 2025 |
Methods — techniques the papers use, named apart from their topics
photorealistic rendering · 1.7external localization · 1.73d gaussian splatting · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | VizFlyt: Perception-centric Pedagogical Framework For Autonomous Aerial RobotsabstractAutonomous aerial robots are becoming commonplace in our lives. Hands-on aerial robotics courses are pivotal in training the next-generation workforce to meet the growing market demands. Such an efficient and compelling course depends on a reliable testbed. In this paper, we present VizFlyt, an open-source perception-centric Hardware-In- The-Loop (HITL) photorealistic testing framework for aerial robotics courses. We utilize pose from an external localization system to hallucinate real-time and photorealistic visual sensors using 3D Gaussian Splatting. This enables stress-free testing of autonomy algorithms on aerial robots without the risk of crashing into obstacles. We achieve over 100Hz of system update rate. Lastly, we build upon our past experiences of offering hands-on aerial robotics courses and propose a new open-source and open-hardware curriculum based on VizFlyt for the future. We test our framework on various course projects in real-world HITL experiments and present the results showing the efficacy of such a system and its large potential use cases. Code, datasets, hardware guides and demo videos are available at https://pear.wpi.edu/research/vizfiyt.html Kushagra Srivastava, Rutwik Kulkarni, Manoj Velmurugan, Nitin J. Sanker |
ICRA | 2 |