
This paper is a study of 2D manipulation without sensing and planning, by exploring the effects of unplanned randomized action sequences on 2D object pose uncertainty. Our approach follows the work of Erdmann and Mason’s sensorless reorienting of an object into a completely determined pose, regardless of its initial pose. While Erdmann and Mason proposed a method using Newtonian mechanics, this paper shows that under some circumstances, a long enough sequence of random actions will also converge toward a determined final pose of the object. This is verified through several simulation and real robot experiments where randomized action sequences are shown to reduce entropy of the object pose distribution. The effects of varying object shapes, action sequences, and surface friction are also explored.
FOS: Computer and information sciences, probabilistic reasoning, automation, Science, Physics, QC1-999, Q, Astrophysics, Article, QB460-466, Computer Science - Robotics, manipulation, manufacturing and logistics, Robotics (cs.RO), probabilistic reasoning, automation
FOS: Computer and information sciences, probabilistic reasoning, automation, Science, Physics, QC1-999, Q, Astrophysics, Article, QB460-466, Computer Science - Robotics, manipulation, manufacturing and logistics, Robotics (cs.RO), probabilistic reasoning, automation
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
