Papers
13
Total Citations
90
H-Index
5
About
Edwin Babaians is a robotics researcher whose work bridges the critical gap between human intent and robotic action, with a focus on teleoperation, shared autonomy, and human-robot interaction. His major contributions span three key areas: developing high-performance interfaces for robot simulation (his most cited work, "ROS2Unity3D," with 17 citations), advancing shared control for manipulator teleoperation through real-time skill refinement ("Skill-CPD," 12 citations), and tackling complex manipulation tasks like liquid pouring using curriculum-based reinforcement learning ("PourNet," 12 citations). Babaians has also made notable contributions to robust state estimation, including novel sensor fusion techniques for indoor heading estimation using skewed-redundant magnetic and inertial sensors. His work on proactive channel state information prediction ("PEACH") addresses critical challenges in ultra-reliable low-latency communications for dynamic environments. With multiple papers accumulating 12+ citations each, Babaians demonstrates consistent impact across simulation interfaces, teleoperation, and sensor fusion. His development of the ReMoRo mobile robot platform further showcases his commitment to practical, educational robotics. Through his research, Babaians continues to push the boundaries of how robots can understand and respond to human operators in real-time, complex environments.
Research Focus
Key Achievements
Top Papers
- 1ROS2Unity3D; High-Performance Plugin to Interface ROS with Unity3d engine17 citations · 2018
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- 10ISSC: Interactive Semantic Shared Control for Haptic Teleoperation3 citations · 2023