Simulation and optimization of inverse kinematics algorithms for real-time target tracking in inertial stabilization platforms

Abstract

Two-axis gimbal systems are engineered to maintain visual lock on target objects by actively counterbalancing movements, regardless of whether these originate from the target or the mounting platform. This research investigates the creation and refinement of inverse kinematics (IK) algorithms for achieving accurate, instantaneous target tracking in inertial stabilization platforms (ISPs), commonly referred to as gimbal systems. Such platforms are essential in applications requiring exceptional stability and precision, including surveillance operations, navigational systems, and scientific investigations. The study commences with a comprehensive analysis of the mathematical foundations underlying IK, with particular attention to the challenges posed by real-time processing requirements. To address these obstacles, sophisticated optimization methods are employed, with an emphasis on reducing computational latency and improving tracking accuracy. The developed algorithms are tested within a Simscape Multibody simulation environment, enabling thorough evaluation across various operational scenarios. Validation incorporates both simulated conditions and practical field tests to confirm the algorithms' durability and functional effectiveness. Results demonstrate significant improvements in both tracking precision and system reactivity, providing a foundation for more efficient and reliable gimbal systems in challenging dynamic environments.