Papers
32
Total Citations
1,395
H-Index
16
About
Hriday Bavle is a robotics researcher whose work sits at the intersection of autonomous aerial systems, simultaneous localization and mapping (SLAM), and human-robot interaction. His research has made substantial contributions to enabling unmanned aerial vehicles (UAVs) to operate intelligently and independently in complex, real-world environments. Among his most influential contributions is pioneering the application of deep reinforcement learning to UAV autonomous landing on moving platforms, work that has accumulated over 220 citations and helped define a new paradigm in vision-based aerial control. His development of fully autonomous aerial robots for indoor search and rescue, alongside the widely adopted AEROSTACK open-source framework, has provided the robotics community with practical tools for deploying aerial systems at scale. Bavle has also advanced the field of semantic SLAM through works like VPS-SLAM and situational graphs, bridging low-level localization with high-level scene understanding. His comprehensive survey on Visual SLAM trends, cited over 110 times, reflects his role as a synthesizer of rapidly evolving research. More recently, his work connecting SLAM to situational awareness signals a broader ambition: giving robots the contextual intelligence needed for truly autonomous decision-making.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Natural user interfaces for human-drone multi-modal interaction176 citations · 2016
- 4Visual SLAM: What Are the Current Trends and What to Expect?111 citations · 2022
- 5VPS-SLAM: Visual Planar Semantic SLAM for Aerial Robotic Systems94 citations · 2020
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- 7
- 8From SLAM to Situational Awareness: Challenges and Survey60 citations · 2023
- 9
- 10Situational Graphs for Robot Navigation in Structured Indoor Environments53 citations · 2022