• The Journal of Korea Robotics Society
• /
• v.17 no.1
• /
• pp.16-24
• /
• 2022

This paper presents a method that can reduce the computational cost of the hierarchical quadratic programming (HQP)-based robot controller. Hierarchical controllers can effectively manage articulated robots with many degrees of freedom (DoFs) to perform multiple tasks. The HQP-based controller is one of the generic hierarchical controllers that can provide a control solution guaranteeing strict task priority while handling numerous equality and inequality constraints. However, according to a large amount of computation, it can be a burden to use it for real-time control. Therefore, for practical use of the HQP, we propose a method to reduce the computational cost by decreasing the size of the decision variable. The computation time and control performance of the proposed method are evaluated by real robot experiments with a 15 DoFs dual-arm manipulator.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.12
• /
• pp.1196-1203
• /
• 2014

Recently, UFRs (Unmanned Flying Robots) have begun to be utilized in various areas for civilian and military applications. Due to this increased utilization, accidents involving UFRsare also increasing. To prevent or monitor accidents caused by UFRs, high-accuracy positioning information is one of the most important technical elements. This paper proposes an efficient UFR monitoring system which provides accurate UFR positioning information with low-cost onboard elements; a small ARM module based on an embedded Linux operating system, a low-cost single frequency GPS receiver with a cheap patch antenna, and a versatile wireless network interface module. The ground monitoring system employs a dual frequency GPS receiver to generate exact UFR coordinates with cm-level accuracy. By processing the UFR measurements based on the Inverse RTK (Real Time Kinematic) method, the ground monitoring system determines the cm-level accurate coordinates of the UFR. The feasibility of the proposed UFR monitoring system was evaluated by three experiments in terms of data loss and accuracy.