Laxman Singh

Jaypee Institute of Information Technology, Rensselaer Polytechnic Institute

Papers

Total Citations

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About

Laxman Singh is a researcher whose work spans autonomous robotics, path planning, and optimization algorithms, with a particular focus on enabling intelligent navigation for robotic systems. His most influential contribution, "Path Planning for the Autonomous Robots Using Modified Grey Wolf Optimization Approach" (2021), has garnered 50 citations and demonstrates his expertise in adapting metaheuristic algorithms to solve complex real-world navigation challenges. By modifying the Grey Wolf Optimization (GWO) algorithm, Singh addressed critical constraints in robotic mobility including power efficiency and environmental adaptability, pushing the boundaries of what autonomous systems can achieve. His comparative study of metaheuristic algorithms (2020, 17 citations) further establishes his role in rigorously evaluating optimization strategies for discrete search-space problems in robotics. Earlier work on variably-autonomous manipulation (2002) reveals a longstanding commitment to human-robot collaboration, particularly in dangerous or physically demanding environments where robots serve as assistants rather than replacements. Across his career, Singh has consistently advanced the theoretical and practical foundations of autonomous robot navigation, making his research valuable to engineers, computer scientists, and robotics students seeking to understand intelligent path-planning methodologies.