Ricardo Bedin Grando
Universidade Federal do Rio Grande, Universidad ORT Uruguay, Universidade Federal de Santa Maria
Papers
22
Total Citations
357
H-Index
8
About
Ricardo Bedin Grando is a robotics researcher whose work spans autonomous navigation, deep reinforcement learning, and hybrid unmanned vehicles. He is perhaps best known for his contributions to mapless navigation systems, where his 2021 paper on Soft Actor-Critic for mobile robot navigation has accumulated 93 citations, establishing him as a significant voice in learning-based robot motion planning. His research extends naturally into aerial robotics, with multiple highly cited works applying deep reinforcement learning to UAV navigation in complex, unstructured environments without reliance on pre-built maps. Grando has also pioneered work on hybrid aerial-underwater vehicles, introducing the HyDrone concept — a novel platform capable of transitioning between aerial and aquatic environments — alongside trajectory planning methods that enable smooth media transitions, collectively gathering over 75 citations. More recently, he has ventured into cutting-edge neural network architectures, exploring Kolmogorov-Arnold Networks as function approximators for online reinforcement learning, demonstrating a forward-thinking approach to AI-driven robotics. His broader portfolio includes human-robot social interaction platforms and immersive simulation frameworks, reflecting a researcher whose curiosity crosses disciplinary boundaries. With a cumulative citation count exceeding 300, Grando's work continues to shape autonomous systems research across land, air, and water.
Research Focus
Key Achievements
Top Papers
- 1Soft Actor-Critic for Navigation of Mobile Robots93 citations · 2021
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- 6Kolmogorov-Arnold Networks for Online Reinforcement Learning19 citations · 2024
- 7Jubileo: An Immersive Simulation Framework for Social Robot Design18 citations · 2023
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