Kshitija Deshmukh
Papers
2
Total Citations
4
H-Index
2
About
Kshitija Deshmukh’s research centers on dynamic trajectory planning for autonomous mobile robotics, with a particular focus on nonholonomic systems intercepting moving targets. Her major contributions involve the use of cubic Bézier curves to generate and adapt paths in real time, enabling robots to respond to changing target locations while maintaining smooth, continuous motion. In her 2016 paper, she introduced a method that leverages overhead camera data to compute initial trajectories and then dynamically alters them, achieving effective interception. Her 2017 follow-up work advanced the field by providing a comparative energy analysis, quantifying power consumption under different velocity and continuity constraints. Though her most-cited papers each have 2 citations, their impact lies in laying foundational groundwork for energy-efficient, real-time path adaptation—a critical challenge in autonomous navigation. Deshmukh’s work bridges control theory and practical robotics, offering insights that inform subsequent research in dynamic environments. Her achievements demonstrate a methodical approach to optimizing both performance and energy use, making her contributions valuable for students and engineers developing agile, power-aware mobile robots.
Research Focus
Key Achievements
Top Papers
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- 2