Optimization of Hybrid Systems with Known Paths

Abstract

In this paper we study a subset of hybrid systems and present a generalized method for their optimization. We outline Hybrid Cost Automata (HCA), an extension to Hybrid Automata, where discrete and continuous cost expressions are added. The class of hybrid systems with known spatial paths is defined in the context of HCA. This type of system is common in industry where for example AGVs transport goods from one location to another, or manipulators move between joint coordinates. The optimization is performed using Dynamic Programming as a preprocessing step, whereafter Mixed Integer Nonlinear Programming is used for scheduling. A case study of a four robot cell is presented with energy consumption used as a minimization criterion.

A Review on Energy-Saving Optimization Methods for Robotic and Automatic Systems

“…Operations scheduling is a further approach related to the motion planning modification that can be found in literature, which saves energy by reducing the energy consumption of a single robotic system or a robotic cell [61][62][63][64][65][66][67][76][77][78]88,89,91,92]. In a robotic cell, a robot works synchronously with other robots or mechatronic systems, and the whole work has to be balanced in order to avoid queues.…”

“…Wigstrom and Lennartson [61] prove the improvements that the new method can give when considering a two-degrees-of-freedom planar manipulator. In [62][63][64], it is also applied to a generic robotic cell.…”

“…Also in this case, the optimization can be performed only on a selection of paths in order not to affect the manufacturing process' efficiency and robustness. In [61][62][63][64], an improved method, called dynamic time scaling, is considered. This exploits dynamic programming, instead of the linear assumption adopted in the previous method, to further reduce energy consumption.…”

“…Thus, a robot waits for the completion of the previous robotic operation before executing its task in order to avoid collisions. The scheduling approach focuses on the optimization of the robot cell operations as a whole, and two main methods can be found: time scaling [61][62][63][64][65][76][77][78] and sequence scheduling [66,67,88,89,91].…”