Shikhar Sharma

Papers

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About

Shikhar Sharma is a researcher in robotics and artificial intelligence, with a primary focus on multi-robot systems and multi-objective optimization. His most cited work, "Parallel multi-objective multi-robot coalition formation" (2015), has garnered 35 citations and addresses the critical challenge of efficiently coordinating teams of robots to achieve multiple, often conflicting, objectives simultaneously. Sharma’s major contribution lies in developing parallel algorithms that enable robots to form optimal coalitions in real-time, balancing trade-offs between task completion time, resource usage, and mission success. This work has practical implications for search-and-rescue operations, warehouse automation, and environmental monitoring, where robot teams must adapt quickly to dynamic conditions. By integrating multi-objective optimization with parallel computing, Sharma has advanced the scalability and robustness of robotic coordination. His research is particularly notable for bridging theoretical optimization techniques with real-world deployment challenges, making it a valuable reference for students and engineers designing autonomous multi-robot systems. Sharma’s work continues to influence the field of distributed robotics, offering a foundation for future innovations in cooperative autonomy.