Victor Augusto Kich
Papers
18
Total Citations
243
H-Index
7
About
Victor Augusto Kich is a robotics and artificial intelligence researcher whose work sits at the intersection of deep reinforcement learning, autonomous navigation, and human-robot interaction. He is best known for pioneering applications of state-of-the-art reinforcement learning algorithms to mobile robot and unmanned aerial vehicle (UAV) navigation, with his 2021 paper on Soft Actor-Critic for mobile robot navigation accumulating 93 citations and establishing him as a leading voice in mapless navigation research. His contributions extend to 3D UAV navigation using double critic architectures and hybrid aerial-underwater vehicles, demonstrating a remarkable breadth across robotic platforms. Kich has also pushed methodological boundaries by investigating the use of Kolmogorov-Arnold Networks as efficient alternatives to traditional neural network architectures in online reinforcement learning settings. Beyond navigation, he has made meaningful contributions to social robotics, developing immersive simulation frameworks and virtual reality platforms for testing human-robot interaction. His comparative analyses of object detection models like YOLOv5 and YOLOv8 in dynamic robotic environments further illustrate his commitment to practical, deployable robotics solutions. With over 200 cumulative citations across a diverse and growing body of work, Kich represents a dynamic and versatile presence in modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1Soft Actor-Critic for Navigation of Mobile Robots93 citations · 2021
- 2
- 3Kolmogorov-Arnold Networks for Online Reinforcement Learning19 citations · 2024
- 4Jubileo: An Immersive Simulation Framework for Social Robot Design18 citations · 2023
- 5
- 6
- 7
- 8
- 9
- 10