A GSPN Software Framework to Model and Analyze Robot Tasks

摘要

In this paper we introduce a software framework to represent robot task plans based on generalized stochastic Petri nets. Our framework allows modeling and analysis of a robot task, providing structural and performance metrics of the designed Petri net, making it a systematic design-analysis-design tool, that leads to improved task plans before execution in real robots. Results of a case study with multiple robots in a virtual scenario show the ability of the framework to provide metrics and relevant properties of the designed task, and how to quickly optimize it.