Mukhtar Sani

Grenoble Images Parole Signal Automatique, Centre National de la Recherche Scientifique, Institut polytechnique de Grenoble

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Total Citations

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About

Mukhtar Sani is a robotics and control systems researcher whose work sits at the intersection of autonomous mobile robotics, game theory, and model predictive control. His research primarily focuses on pursuit-evasion games and obstacle avoidance strategies for nonholonomic mobile robots, applying sophisticated mathematical frameworks to solve complex multi-agent competitive scenarios. Sani's most significant contributions center on developing Nonlinear Model Predictive Control (NMPC) methodologies for autonomous systems. His 2020 study on pursuit-evasion games for nonholonomic robots, which has garnered 22 citations, demonstrated how NMPC can effectively coordinate competitive robotic interactions while simultaneously managing obstacle avoidance — a challenging real-world problem. Building on this foundation, his 2021 work on game-theoretic and model predictive control algorithms (17 citations) advanced strategies for non-cooperative game scenarios where opponents' strategies must be predicted with limited information. His 2021 research on dynamic obstacle avoidance using NMPC (15 citations) further showcased his ability to bridge theoretical control frameworks with practical robotic implementation. Most recently, his 2023 work introduced real-time game-theoretic MPC for target defense scenarios, with direct applications in military and security contexts. Collectively accumulating over 60 citations, Sani's research represents meaningful advances in intelligent autonomous systems operating in adversarial and dynamic environments.