What is Hierarchical Quadratic Programming?
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Hierarchical Quadratic Programming (HQP) is a powerful optimization approach utilized in various fields like Human-Robot Collaboration (HRC), multi-robot systems, and humanoid robot motion planning. HQP enables the computation of solutions for strictly prioritized tasks by formulating them as quadratic programs. It is particularly effective in scenarios where tasks have different levels of priority, such as in cooperative logistics missions, where tasks are defined as equality and inequality constraints with varying importance levels . HQP also plays a crucial role in achieving real-time optimization in humanoid robot motion planning by utilizing a hierarchical structure that allows for strict task prioritization, ensuring stability and efficiency in controlling robots with high degrees of freedom .
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31 Jan 2019 26 Citations | Hierarchical Quadratic Programming (HQP) efficiently handles strictly prioritized tasks in robot control, ensuring smooth task transitions without control input discontinuity, as outlined in the research paper. |
24 Jun 2021 | Hierarchical Quadratic Programming (HQP) is a control optimization method used in multi-robot systems to solve for control inputs based on strict priority levels of tasks with equality and inequality constraints. |
01 Dec 2022 | Hierarchical Quadratic Programming is a control framework integrating human ergonomics in Human-Robot Collaboration, optimizing tasks by combining industrial parameters with human comfort for improved efficiency and health. |
Open access•Posted Content | Hierarchical Quadratic Programming is a novel approximation hierarchy for cardinality-constrained, convex quadratic programs that efficiently screens potential indices of nonzero elements, preserving convexity in continuous variables. |
| Hierarchical Quadratic Programming is utilized in the paper for robot whole-body control, prioritizing tasks. It optimizes dynamic equations efficiently, reducing the need for multiple optimizations. |
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