Sivasankar Ganesan
Papers
9
Total Citations
165
H-Index
6
About
Sivasankar Ganesan is a robotics and autonomous systems researcher whose work centers on motion planning, path optimization, and intelligent navigation for autonomous mobile robots. He has dedicated much of his career to advancing sampling-based path planning algorithms, particularly variants of the Rapidly Exploring Random Tree (RRT*) framework. His most influential contribution, a hybrid sampling-based RRT* algorithm published in 2024, has already amassed 96 citations, reflecting the research community's enthusiastic reception of his innovations. Through a series of systematic enhancements — including goal-oriented sampling strategies, directional sampling methods, and improved initial cost solutions — Ganesan has consistently addressed core limitations of classical RRT* algorithms, such as slow convergence rates and suboptimal path solutions in cluttered environments. His 2022 work on global path planning further demonstrated his commitment to practical, real-world applicability. Beyond purely algorithmic contributions, Ganesan has explored multi-robot swarm exploration, hardware-in-the-loop simulation for robotic control, and has authored comprehensive reviews of hybrid path planning approaches. With a growing publication record spanning 2020 to 2025 and over 160 cumulative citations, he is establishing himself as a significant voice in autonomous mobile robotics research.
Research Focus
Key Achievements
Top Papers
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