Collision-free path coordination and cycle time optimization of industrial robot cells
Doctoral thesis, 2021

In industry, short ramp-up times, product quality, product customization and high production rates are among the main drivers of technological progress. This is especially true for automotive manufacturers whose market is very competitive, constantly pushing for new solutions. In this industry, many of the processes are carried out by robots: for example, operations such as stud/spot welding, sealing, painting and inspection. Besides higher production rates, the improvement of these processes is important from a sustainability perspective, since an optimized equipment utilization may be achieved, in terms of resources used, including such things as robots, energy, and physical prototyping.

The achievements of such goals may, nowadays, be reached also thanks to virtual methods, which make modeling, simulation and optimization of industrial processes possible. The work in this thesis may be positioned in this area and focuses on virtual product and production development for throughput improvement of robotics processes in the automotive industry. Specifically, the thesis presents methods, algorithms and tools to avoid collisions and minimize cycle time in multi-robot stations. It starts with an overview of the problem, providing insights into the relationship between the volumes shared by the robots' workspaces and more abstract modeling spaces. It then describes a computational method for minimizing cycle time when robot paths are geometrically fixed and only velocity tuning is allowed to avoid collisions.

Additional requirements are considered for running these solutions in industrial setups, specifically the time delays introduced when stopping robots to exchange information with a programmable logic controller (PLC). A post-processing step is suggested, with algorithms taking into account these practical constraints. When no communication at all with the PLC is highly desirable, a method of providing such programs is described to give completely separated robot workspaces. Finally, when this is not possible (in very cluttered environments and with densely distributed tasks, for example), robot routes are modified by changing the order of operations to avoid collisions between robots.

In summary, by requiring fewer iterations between different planning stages, using automatic tools to optimize the process and by reducing physical prototyping, the research presented in this thesis (and the corresponding implementation in software platforms) will improve virtual product and production realization for robotic applications.

cycle time optimization

multi-robot collision avoidance

production planning

multi-robot routing and coordination

Virtual Development Laboratory, Chalmers, Hörsalsvägen 11, Göteborg
Opponent: Prof. Steven M. LaValle, Center for Ubiquitous Computing, University of Oulu, Finland

Author

Domenico Spensieri

Fraunhofer-Chalmers Centre

Chalmers, Industrial and Materials Science, Product Development

An Iterative Approach for Collision Free Routing and Scheduling in Multirobot Stations

IEEE Transactions on Automation Science and Engineering,; Vol. 13(2016)p. 950-962

Journal article

Collision-free robot coordination and visualization tools for robust cycle time optimization

Journal of Computing and Information Science in Engineering,; Vol. 21(2021)

Journal article

Modeling and optimization of implementation aspects in industrial robot coordination

Robotics and Computer-Integrated Manufacturing,; Vol. 69(2021)

Journal article

Intersection-Free Geometrical Partitioning of Multirobot Stations for Cycle Time Optimization

IEEE Transactions on Automation Science and Engineering,; (2018)

Journal article

Coordination of robot paths for cycle time minimization

IEEE International Conference on Automation Science and Engineering,; (2013)

Paper in proceeding

In industry, today, short time-to-market, excellent product quality, large product customization and high production rates are among the main drivers of technological progress. Besides them, the improvement of industrial processes is important from a sustainability perspective, in terms of resources used, such as energy, machines and physical prototyping.

The achievements of such goals may, nowadays, be reached also thanks to virtual methods, which make modeling, simulation and optimization of industrial processes possible. The work in this thesis may be positioned in this area and focuses on virtual product and production development for throughput improvement of processes in the automotive industry. Here, many of the processes are carried out by robots: for example, operations such as stud/spot welding, sealing, painting and inspection.

Specifically, this thesis presents methods and tools to avoid collisions and minimize cycle time in multi-robot stations. It presents algorithms to assign operations to specific robots, decide in which order these operations should be carried out and tune robot velocities. The purpose is to generate optimal robot programs, which aim to achieve the overall goals defined above.

In summary, by requiring fewer iterations between different planning stages, by using automatic tools to optimize the process and by reducing physical prototyping, the research presented in this thesis (and the corresponding implementation in software platforms) aims to improve virtual product and production realization for robotic applications.

Smart Assembly 4.0

Swedish Foundation for Strategic Research (SSF) (RIT15-0025), 2016-05-01 -- 2021-06-30.

Subject Categories

Production Engineering, Human Work Science and Ergonomics

Robotics

Computer Systems

Driving Forces

Sustainable development

Areas of Advance

Production

ISBN

978-91-7905-579-0

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5046

Publisher

Chalmers University of Technology

Virtual Development Laboratory, Chalmers, Hörsalsvägen 11, Göteborg

Online

Opponent: Prof. Steven M. LaValle, Center for Ubiquitous Computing, University of Oulu, Finland

More information

Latest update

10/18/2021