Multi-Level Autonomy Robot Telesupervision
Gregg Podnar, John M. Dolan, Alberto Elfes, Marcel Bergerman
- Year
- 2018
- Citations
- 5
- Access
- Open access
Abstract
This paper focuses on the development of an advanced telesupervision system architecture that supports a highly efficient approach to human-robot interaction while allowing heterogeneous robotic assets to be deployed. The described multi-level framework not only supports human monitoring and control of existing state-of-the-art autonomous agents, but also allows new autonomous agents to be incorporated at each level as they become available. Our philosophy of maximizing the efficiency and safety of humans through telesupervision of autonomous robotic systems is applicable in extreme environments on Earth, and across space including telesupervising Lunar and Martian robots when humans are nearby. We describe two applications of our Multilevel-Autonomy Robot Telesupervision Architecture: for planetary mineralprospecting using multiple semi-autonomous rovers conducted under a past project funded by the NASA Exploration Systems Mission Directorate; and for Harmful Algal Bloom detection and characterization by multiple semi-autonomous ocean vessels conducted under an ongoing project funded by the NASA Earth Science Technology Office.
Keywords
Related papers
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