Subham Agarwal

Papers

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About

Subham Agarwal’s research focuses on advancing autonomous navigation and path planning for mobile robots, with a particular emphasis on optimizing soft computing algorithms. His most cited work, “Path Planning of Mobile Robot Using PSO Algorithm” (2018, 12 citations), demonstrates his foundational contributions to applying particle swarm optimization (PSO) for efficient robot trajectory design. Agarwal’s key innovation lies in upgrading traditional PSO into adaptive particle swarm optimization (APSO), as detailed in his 2019 paper “An Effective Track Designing Approach for a Mobile Robot.” This approach enhances accuracy by dynamically adjusting parameters in response to real-time environmental changes, addressing the growing demand for smarter, more responsive autonomous systems. By integrating APSO into track designing, Agarwal has provided a scalable solution for improving mobile robot performance in complex settings. His work bridges theoretical optimization with practical robotics, offering a robust framework for future research in adaptive navigation. With a growing citation record, Agarwal’s contributions are gaining recognition among scholars exploring intelligent control systems and autonomous vehicle technologies.