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About

Puneet Singla is a leading researcher in nonlinear control, autonomous systems, and sensor-based robotics, with a focus on optimizing the performance of complex dynamical systems under uncertainty. His work bridges theoretical advances in optimal control and information theory with practical applications in aerospace and robotic systems. Singla’s most-cited paper introduces a sequential linear programming method for designing time-optimal controllers for nonlinear systems, a contribution that has garnered 13 citations and provides a computationally efficient approach for trajectory optimization. He has also made significant strides in active sensing, as demonstrated by his 2013 paper on optimal information collection for nonlinear systems, which uses mutual information to guide sensor deployment for multiple target tracking and localization (12 citations). In the realm of robotics, Singla’s 2017 work on visual feedback control of tensegrity robotic systems addresses the unique challenges of maintaining stability through positive string tensions (11 citations). Additionally, his 2009 contribution to the LandingNav project—a precision autonomous landing sensor for planetary bodies—showcases his impact on space exploration, enabling safer landings on extraterrestrial surfaces. With a career marked by innovative solutions to real-world control and sensing problems, Singla’s research continues to influence autonomous navigation and robotic systems.