Purpose
This paper aims to present an approach for the simulation of a heterogeneous robotic cell. The simulation enables the cell’s developers to conveniently compare the performance of alternative cell configurations. The approach combines the use of multiple available simulation tools, with a custom holonic cell controller. This overcomes the limitation of currently available robot simulation packages by allowing integration of multiple simulation tools including multiple vendor simulation packages.
Design/methodology/approach
A feeding cell was developed as a case study representing a typical robotic application. The case study would compare two configurations of the cell, namely, eye-in-hand vision and fixed-camera vision. The authors developed the physical cell in parallel with the simulated cell to validate its performance. Then they used simulation to scale the models (by adding subsystems) and shortlist suitable cell configurations based on initial capital investment and throughput rate per unit cost. The feeding cell consisted of a six-degree of freedom industrial robot (KUKA KR16), two smart cameras (Cognex ism-1100 and DVT Legend 500), an industrial PC (Beckhoff) and custom reconfigurable singulation units.
Findings
The approach presented here allows the combination of dissimilar simulation models constructed for the above mentioned case study. Experiments showed the model developed in this approach could reasonably predict various eye-in-hand and fixed-camera systems’ performance. Combining the holonic controller with the simulation allows developers to easily compare the performance of a variety of configurations. The use of a common communication platform allowed the communication between multiple simulation packages, allowing multi-vendor simulation, thereby overcoming current limitation in simulation software.
Research limitations/implications
The case study developed here is considered a typical feeding and assembly application. This is however very different from other robotic applications which should be explored in separate case studies. Simulation packages with the same communication interface as the physical resource can be integrated. If the communication interface is not available, other means of simulation can be used. The case study findings are limited to the specific products being used and their simulation packages. However, these are indicative of typical industry technologies available. Only real-time simulations were considered.
Practical implications
This simulation-based approach allows designers to quickly quantify the performance of alternative system configurations (eye-in-hand or fixed camera in this case) and scale, thereby enabling them to better optimize robotic cell designs. In addition, the holonic control system’s modular control interface allows for the development of the higher-level controller without hardware and easy replacement of the lower level components with other hardware or simulation models.
Originality/value
The combination of a holonic control system with a simulation to replace hardware is shown to be a useful tool. The inherent modularity of holonic control systems allows that multiple simulation components be connected, thereby overcoming the limitation of vendor-specific simulation packages.
A Simulation-Based Dynamic Programming Method for Interchange Scheduling of Port Collecting and Distributing Network
