Navin Singhaniya

Papers

Total Citations

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About

Navin Singhaniya is a researcher in human-robot interaction, with a focus on embodied artificial intelligence and autonomous decision-making systems. His most cited work, "A Novel Framework for Robotic Chess" (2021), addresses a challenging domain in robotics: enabling a system to perceive, reason, and physically act within a dynamic, rule-based environment. Singhaniya’s framework integrates computer vision for board-state detection, algorithmic move generation, and robotic manipulation to execute plays—effectively bridging the gap between abstract AI planning and real-world physical interaction. While his citation count is currently modest, his contribution is notable for tackling the full perception-action loop in a constrained but complex setting, laying groundwork for more adaptive human-robot collaborative systems. This work signals a promising trajectory in robotic cognition and interactive AI, with potential applications in education, assistive robotics, and automated strategic gameplay. Singhaniya’s research is particularly relevant for students and researchers interested in the intersection of computer vision, planning algorithms, and physical robotics.