Sunil Kumar Dasari

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About

Sunil Kumar Dasari is a robotics researcher whose work bridges computer vision and autonomous navigation. His primary research areas include object detection for robotic systems and intelligent path planning, with a focus on real-world applications in dynamic environments. Dasari’s most notable contribution is his development of a Histogram of Oriented Gradients (HOG)-based object detection framework tailored for soccer-playing robots, published in 2022. This work, which has garnered 3 citations, addresses the challenge of robust visual perception in fast-paced, unpredictable settings, offering a lightweight solution that balances accuracy and computational efficiency—a critical trade-off for embedded robotic platforms. Additionally, his 2020 survey on robot path planning–prediction provides a comprehensive multidisciplinary perspective, synthesizing approaches from control theory, machine learning, and sensor fusion to chart future directions for autonomous navigation. With 2 citations, this review serves as a valuable resource for researchers seeking to integrate prediction and planning in complex terrains. Dasari’s work, though early in its citation impact, demonstrates a clear commitment to advancing practical robotics, making his contributions noteworthy for students and engineers exploring vision-guided autonomy and motion planning in unstructured environments.