Automated Generation of Robotic Planning Domains from Observations
Maximilian Diehl,Chris Paxton,Karinne Ramirez-Amaro,Maximilian Diehl,Chris Paxton,Karinne Ramirez-Amaro
Automated planning enables robots to find plans to achieve complex, long-horizon tasks, given a planning domain. This planning domain consists of a list of actions, with their associated preconditions and effects, and is usually manually defined by a human expert, which is very time-consuming or even infeasible. In this paper, we introduce a novel method for generating this domain automatically fr...
