Temporal Logic (TL)-Based Autonomy for Smart Manufacturing Systems

Abstract

Smart-Manufacturing systems are increasingly being used to perform complex tasks on the factory floor. Most often, these systems have hard-coded cases to achieve a specific set of actions -or to assure the safety of the operations. The hard-coding makes the use complicated to re-deploy a system for different tasks. Therefore, it is necessary to have a flexible framework, which can generate a plan based on an intuitive description with system constraints, while satisfying all safety conditions. In this work, we propose Linear Temporal Logic (LTL)-based autonomy framework for smart-manufacturing systems. Specifically, we describe a general technique for formulating problems using LTL specifications. The use of LTL enables us to specify a manufacturing scenario (e.g. assembly), along with system constraints, as well as assured autonomy. Based on the given LTL formulation, a safe solution satisfying all constraints can be generated using a satisfiability solver. To eliminate the exhaustive and exponential nature of the solver, we reduced the exploration space with a divide and conquer approach in a receding horizon, which brings dramatic improvements in time and enables our solution for real-world applications. Our experimental evaluations indicated that our solution scales linearly as the problem complexity increases. We showcased the feasibility of our approach by integrating TLbased autonomy with the simulations of Gantry robot in Siemens NX Mechatronics Concept Designer and TIA Portal (PLCSIM Advanced) for Siemens S7-1500 TCPU connected to Sinamics drives.