Collision-free path coordination and cycle time optimization of industrial robot cells

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\u27 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

Coordination of several robots based on temporal synchronization

© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper proposes an approach to deal with the problem of coordinating multi-robot systems, in which each robot executes individually planned tasks in a shared workspace. The approach is a decoupled method that can coordinate the participating robots in on-line mode. The coordination is achieved through the adjustment of the time evolution of each robot along its original planned geometric path according to the movements of the other robots to assure a collision-free execution of their respective tasks. To assess the proposed approach different tests were performed in graphical simulations and real experiments.Postprint (published version

Mathematical Modelling and Methods for Load Balancing and Coordination of Multi-Robot Stations

The automotive industry is moving from mass production towards an individualized production, individualizing parts aims to improve product quality and to reduce costs and material waste. This thesis concerns aspects of load balancing and coordination of multi-robot stations in the automotive manufacturing industry, considering efficient algorithms required by an individualized production. The goal of the load balancing problem is to improve the equipment utilization. Several approaches for solving the load balancing problem are suggested along with details on mathematical tools and subroutines employed.Our contributions to the solution of the load balancing problem are fourfold. First, to circumvent robot coordination we construct disjoint robot programs, which require no coordination schemes, are flexible, admit competitive cycle times for several industrial instances, and may be preferred in an individualized production. Second, since solving the task assignment problem for generating the disjoint robot programs was found to be unreasonably time-consuming, we model it as a generalized unrelated parallel machine problem with set packing constraints and suggest a tailored Lagrangian-based branch-and-bound algorithm. Third, a continuous collision detection method needs to determine whether the sweeps of multiple moving robots are disjoint. We suggest using the maximum velocity of each robot along with distance computations at certain robot configurations to derive a function that provides lower bounds on the minimum distance between the sweeps. The lower bounding function is iteratively minimized and updated with new distance information; our method is substantially faster than previously developed methods. Fourth, to allow for load balancing of complex multi-robot stations we generalize the disjoint robot programs into sequences of such; for some instances this procedure provides a significant equipment utilization improvement in comparison with previous automated methods

Mathematical Modelling for Load Balancing and Minimization of Coordination Losses in Multirobot Stations

The automotive industry is moving from mass production towards an individualized production, in order to improve product quality and reduce costs and material waste. This thesis concerns aspects of load balancing of industrial robots in the automotive manufacturing industry, considering efficient algorithms required by an individualized production. The goal of the load balancing problem is to improve the equipment utilization. Several approaches for solving the load balancing problem are presented along with details on mathematical tools and subroutines employed.Our contributions to the solution of the load balancing problem are manifold. First, to circumvent robot coordination we have constructed disjoint robot programs, which require no coordination schemes, are more flexible, admit competitive cycle times for some industrial instances, and may be preferred in an individualized production. Second, since solving the task assignment problem for generating the disjoint robot programs was found to be unreasonably time-consuming, we modelled it as a generalized unrelated parallel machine problem with set packing constraints and suggested a tighter model formulation, which was proven to be much more tractable for a branch--and--cut solver. Third, within continuous collision detection it needs to be determined whether the sweeps of multiple moving robots are disjoint. Our solution uses the maximum velocity of each robot along with distance computations at certain robot configurations to derive a function that provides lower bounds on the minimum distance between the sweeps. The lower bounding function is iteratively minimized and updated with new distance information; our method is substantially faster than previously developed methods

Optimal Robot Placement for Tasks Execution

AbstractAutomotive assembly cells are cluttered environments, including robots, workpieces, and fixtures. Due to high volumes and several product variants assembled in the same cell, robot placement is crucial to increase flexibility and throughput. In this paper, we propose a novel method to optimize the base position of an industrial robot with the objective to reach all predefined tasks and minimize cycle time: robot inverse kinematics and collision avoidance are integrated together with a derivative-free optimization algorithm. This approach is successfully used to find feasible solutions on industrial test cases, showing up to 20% cycle time improvement

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

This work is inspired by the problem of planning sequences of operations, as welding, in car manufacturing stations where multiple industrial robots cooperate. The goal is to minimize the station cycle time, \emph{i.e.} the time it takes for the last robot to finish its cycle. This is done by dispatching the tasks among the robots, and by routing and scheduling the robots in a collision-free way, such that they perform all predefined tasks. We propose an iterative and decoupled approach in order to cope with the high complexity of the problem. First, collisions among robots are neglected, leading to a min-max Multiple Generalized Traveling Salesman Problem (MGTSP). Then, when the sets of robot loads have been obtained and fixed, we sequence and schedule their tasks, with the aim to avoid conflicts. The first problem (min-max MGTSP) is solved by an exact branch and bound method, where different lower bounds are presented by combining the solutions of a min-max set partitioning problem and of a Generalized Traveling Salesman Problem (GTSP). The second problem is approached by assuming that robots move synchronously: a novel transformation of this synchronous problem into a GTSP is presented. Eventually, in order to provide complete robot solutions, we include path planning functionalities, allowing the robots to avoid collisions with the static environment and among themselves. These steps are iterated until a satisfying solution is obtained. Experimental results are shown for both problems and for their combination. We even show the results of the iterative method, applied to an industrial test case adapted from a stud welding station in a car manufacturing line