Reactive Task Adaptation Based on Hierarchical Constraints Classification for Safe Industrial Robots
Nicola Maria Ceriani, Andrea Maria Zanchettin, Paolo Rocco, Andreas Stolt, Anders Robertsson
- 发表年份
- 2015
- 引用次数
- 39
摘要
A widespread and flexible use of robots in rapidly changing working environments could be greatly enhanced by human-robot interaction and collaboration. Humans and robots have complementary skills. The robotic worker can relieve the human from repetitive work, and the human can make robot deployment easier by managing nonstandard or particularly skilful operations. Such a scenario, however, requires new safety systems to preserve human workers from potential danger and at the same time to make human-robot interaction productive and advantageous. In this paper, a system for safe and task consistent human-robot interaction integrated with an industrial controller is proposed. The robot executes evasive motions to avoid impacts with obstacles consistently with the task. A classification of constraints constituting the task is proposed and a safety strategy based on such classification is defined. This paper finally presents integration of the safety system with an industrial controller and experimental validation on an assembly operation.
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