Hierarchical Least Square Programming

Hierarchical Least Squares Programming (HLSP) is an optimization technique used to solve problems with prioritized objectives, where some goals are more important than others. Current research focuses on efficient algorithms, such as hierarchical Newton's methods and alternating direction methods of multipliers, to improve the speed and numerical stability of HLSP, particularly for applications involving complex robotic systems and dynamic constraints. This approach finds significant application in robotics, enabling tasks like collision avoidance in minimally invasive surgery and human-robot collaboration by allowing robots to prioritize safety and task completion while handling multiple constraints simultaneously.