This chapter presents the core programming‐by‐demonstration (PbD) methods for task modeling at a trajectory level of task abstraction. It describes the most common methods used for task modeling at the low‐level of abstraction. Based on the level of task abstraction, the methods are categorized into high‐level task representation at the symbolic level of abstraction and low‐level task representation at the trajectory level of abstraction. Statistical methods have been widely used in robotics for representing the uncertain information about the state of the environment. The statistical frameworks represent the uncertainties of robot's perception and action via probability distributions, instead of using a single best guess about the state of the world. Regarding robot learning from observation of human demonstrations, the theory of statistical modeling has been exploited for representing the uncertainties of the acquired perceptual data.
Task Modeling
2017-03-10
16 pages
Article/Chapter (Book)
Electronic Resource
English
Task Modeling for Lunar Landing Point Redesignation
AIAA | 2009
|Modeling and Simulation for Helicopter Task Analysis
Online Contents | 2002
|Task Modeling for Lunar Landing Point Redesignation
British Library Conference Proceedings | 2009
|MODELING AND SIMULATION FOR HELICOPTER TASK ANALYSIS
British Library Conference Proceedings | 2001
|Modeling Driver Behavior as Sequential Risk-Taking Task
Transportation Research Record | 2008
|