Julia G. Kokunko
Papers
4
Total Citations
23
H-Index
3
About
Julia G. Kokunko is a robotics researcher specializing in motion planning and control for autonomous wheeled vehicles and manipulators. Her work focuses on generating smooth, achievable trajectories from discrete waypoints, addressing the critical challenge of transforming path sequences into continuous curves that respect physical constraints. Kokunko’s key contributions include the design of dynamic models for processing motion reference signals, enabling mobile robots to navigate with precision under non-smooth uncertainty. Her 2022 paper on dynamic models for mobile robots has garnered 10 citations, while her 2023 work on direct endpoint control of manipulators under uncertainty has received 7 citations. Notably, her 2023 study on generating achievable three-dimensional trajectories via tracking differentiators (4 citations) proposes novel algorithms for automatic smoothing, and her 2024 paper on smooth reference trajectories for unmanned wheeled platforms (2 citations) introduces spline interpolation techniques that stitch route sections while automatically constraining velocity, acceleration, and jerk. Kokunko’s research is pivotal for advancing autonomous navigation in complex environments, offering practical solutions for real-world deployment of wheeled robots and robotic arms.
Research Focus
Key Achievements
Top Papers
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