Constrained Control of Robotic Manipulators Using the Explicit Reference Governor
Kelly Merckaert, Bram Vanderborght, Marco M. Nicotra, Emanuele Garone
- 发表年份
- 2018
- 引用次数
- 8
摘要
Robotic manipulators that are intended to interact with humans in their operating region are systems that need formal safety guarantees. Current solutions cannot handle both input and state constraints, have difficulties handling nonconvex constraints, or are computationally too expensive. To tackle these drawbacks, we analyzed a constrained control strategy, the Explicit Reference Governor (ERG), which can address both input and state constraints, and does not require any online optimization, thus making it computationally inexpensive. This paper presents the theory of the ERG for a general robotic manipulator and shows simulations for a specific 2DOF planar robotic manipulator. The proposed control scheme is able to steer the robot arm to the desired end-effector position, or an admissible approximation, in the presence of limited joint ranges, actuator saturations, and static obstacles. As a result, the ERG is a promising tool for the control of robotic manipulators subject to constraints.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002