Omanshu Thapliyal
Papers
1
Total Citations
1
H-Index
1
About
Omanshu Thapliyal is a researcher whose work lies at the intersection of robotics, distributed optimization, and multi-agent systems. His key contributions focus on developing scalable algorithms for networks of robots operating under limited information. In his most-cited work, "Path Planning for a Network of Robots with Distributed Multi-Objective Linear Programming" (2021), Thapliyal addresses the fundamental challenge of target pursuit and obstacle avoidance when no single robot has complete knowledge of the environment. By formulating the problem as a distributed multi-objective linear program, he enables robots to share and satisfy obstacle avoidance constraints across the network, achieving coordinated behavior without centralized control. This approach has significant implications for swarm robotics, search-and-rescue missions, and autonomous exploration in unknown terrains. While his citation count is still growing, the novelty of his distributed constraint-sharing framework marks an important step toward robust, scalable multi-robot systems. Thapliyal’s work is particularly relevant for students and researchers interested in decentralized decision-making, optimization under uncertainty, and the practical deployment of robot networks in complex, dynamic environments.
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Top Papers
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