papers AI Learner
The Github is limit! Click to go to the new site.

Toward Achieving Formal Guarantees for Human-Aware Controllers in Human-Robot Interactions

2019-03-04
Rachel Schlossman, Minkyu Kim, Ufuk Topcu, Luis Sentis

Abstract

With the primary objective of human-robot interaction being to support humans’ goals, there exists a need to formally synthesize robot controllers that can provide the desired service. Synthesis techniques have the benefit of providing formal guarantees for specification satisfaction. There is potential to apply these techniques for devising robot controllers whose specifications are coupled with human needs. This paper explores the use of formal methods to construct human-aware robot controllers to support the productivity requirements of humans. We tackle these types of scenarios via human workload-informed models and reactive synthesis. This strategy allows us to synthesize controllers that fulfill formal specifications that are expressed as linear temporal logic formulas. We present a case study in which we reason about a work delivery and pickup task such that the robot increases worker productivity, but not stress induced by high work backlog. We demonstrate our controller using the Toyota HSR, a mobile manipulator robot. The results demonstrate the realization of a robust robot controller that is guaranteed to properly reason and react in collaborative tasks with human partners.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1903.01350

PDF

http://arxiv.org/pdf/1903.01350


Comments

Content