Aadi Kothari
Papers
2
Total Citations
20
H-Index
2
About
Aadi Kothari is a rising researcher at the forefront of safe and robust autonomy, specializing in the tight integration of perception, motion planning, and control for nonlinear robotic systems. His most cited work, "Risk bounded nonlinear robot motion planning with integrated perception & control" (2022, 17 citations), addresses a critical gap in autonomy stacks: the inadequate handling of perception and prediction uncertainties. Rather than relying on simplistic Gaussian assumptions, Kothari develops frameworks that explicitly incorporate these uncertainties to ensure risk-bounded motion planning, a vital contribution for deploying robots in unstructured, real-world environments. In his more recent work, "Enhanced Human-Robot Collaboration using Constrained Probabilistic Human-Motion Prediction" (2023, 3 citations), he tackles the challenge of human-robot interaction by moving beyond purely neural network-based or offline regression models. He proposes a constrained probabilistic approach to human motion prediction, enabling safer and more efficient collaboration. By pioneering methods that mathematically guarantee safety under realistic uncertainty, Kothari is laying the groundwork for the next generation of trustworthy autonomous systems, from manufacturing to field robotics.
Research Focus
Key Achievements
Top Papers
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