Demo Data from EDBT 2026 / reviewers in the wild / expert
David Capek
dblp:399/8748
· DBLP profile ↗
1ranked-venue papers
1as 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 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 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 |
Reinforcement learning · 61% Robot navigation and mapping · 39% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping › mobile robot navigation › mapless navigation
navigation in unknown environments |
0.9 | 1 | 2025 | FlightForge: Advancing UAV Research with Procedural Generation of High-Fidelity Simulation and Integrated Autonomy · ICRA 2025 |
Machine learning › Reinforcement learning › reinforcement learning environment › environment design
procedural environment generation |
0.9 | 1 | 2025 | FlightForge: Advancing UAV Research with Procedural Generation of High-Fidelity Simulation and Integrated Autonomy · ICRA 2025 |
Machine learning › Reinforcement learning › reinforcement learning environment
simulation environment |
0.9 | 1 | 2025 | FlightForge: Advancing UAV Research with Procedural Generation of High-Fidelity Simulation and Integrated Autonomy · ICRA 2025 |
Methods — techniques the papers use, named apart from their topics
sensor simulation · 0.9procedural generation · 0.9photorealistic rendering · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | FlightForge: Advancing UAV Research with Procedural Generation of High-Fidelity Simulation and Integrated AutonomyabstractRobotic simulators play a crucial role in the development and testing of autonomous systems, particularly in the realm of Uncrewed Aerial Vehicles (UAV). However, existing simulators often lack high-level autonomy, hindering their immediate applicability to complex tasks such as autonomous navigation in unknown environments. This limitation stems from the challenge of integrating realistic physics, photorealistic rendering, and diverse sensor modalities into a single simulation environment. At the same time, the existing photorealistic UAV simulators use mostly hand-crafted environments with limited environment sizes, which prevents the testing of long-range missions. This restricts the usage of existing simulators to only low-level tasks such as control and collision avoidance. To this end, we propose the novel FlightForge UAV opensource simulator. FlightForge offers advanced rendering capabilities, diverse control modalities, and, foremost, procedural generation of environments. Moreover, the simulator is already integrated with a fully autonomous UAV system capable of long-range flights in cluttered unknown environments. The key innovation lies in novel procedural environment generation and seamless integration of high-level autonomy into the simulation environment. Experimental results demonstrate superior sensor rendering capability compared to existing simulators, and also the ability of autonomous navigation in almost infinite environments. David Capek, Jan Hrncír, Tomás Báca, Jakub Jirkal, Vojtech Vonásek, Robert Penicka, Martin Saska |
ICRA | 1 |