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About

Vesna Knights is a leading researcher in autonomous mobile robotics, specializing in the intersection of nonlinear dynamics, machine learning, and intelligent control systems for IoT-enabled environments. Her work fundamentally advances how robotic systems perceive, navigate, and coordinate in complex, obstacle-filled settings. Knights pioneered the concept of platoon movement for autonomous vehicles, developing guidance and control systems that enable smart cars to operate in coordinated formations—a contribution with over 13 citations. She has also made significant strides in obstacle avoidance, introducing an innovative potential fields method for mobile robot navigation that has garnered 9 citations. Her recent, highly-cited work (9 citations) integrates nonlinear dynamics with machine learning within an IoT framework, creating adaptable, real-time control systems capable of handling complex environments. Knights’ research on dynamic modeling under disturbances and obstacles (7 citations) provides versatile mathematical models applicable to diverse robotic tasks. Most notably, her 2025 study on symmetry and asymmetry in nonlinear control introduces a neural network-based residual model as a novel control enhancement, pushing the boundaries of Ackermann steering geometry. With a growing citation impact exceeding 39 total citations, Knights continues to shape the future of intelligent, autonomous robotic systems.