| 1. |
- Spensieri, Domenico, 1978, et al.
(författare)
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An Iterative Approach for Collision Free Routing and Scheduling in Multirobot Stations
- 2016
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Ingår i: IEEE Transactions on Automation Science and Engineering. - 1558-3783 .- 1545-5955. ; 13:2, s. 950-962
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Tidskriftsartikel (refereegranskat)abstract
- 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, 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 (B&B) 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.
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| 2. |
- Gleeson, Daniel, 1988, et al.
(författare)
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Generating Optimized Trajectories for Robotic Spray Painting
- 2022
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Ingår i: IEEE Transactions on Automation Science and Engineering. - 1558-3783 .- 1545-5955. ; 19:3, s. 1380-1391
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Tidskriftsartikel (refereegranskat)abstract
- In the manufacturing industry, spray painting is often an important part of the manufacturing process. Especially in the automotive industry, the perceived quality of the final product is closely linked to the exactness and smoothness of the painting process. For complex products or low batch size production, manual spray painting is often used. But in large scale production with a high degree of automation, the painting is usually performed by industrial robots. There is a need to improve and simplify the generation of robot trajectories used in industrial paint booths. A novel method for spray paint optimization is presented, which can be used to smooth out a generated initial trajectory and minimize paint thickness deviations from a target thickness. The smoothed out trajectory is found by solving, using an interior point solver, a continuous non-linear optimization problem. A two-dimensional reference function of the applied paint thickness is selected by fitting a spline function to experimental data. This applicator footprint profile is then projected to the geometry and used as a paint deposition model. After generating an initial trajectory, the position and duration of each trajectory segment are used as optimization variables. The primary goal of the optimization is to obtain a paint applicator trajectory, which would closely match a target paint thickness when executed. The algorithm has been shown to produce satisfactory results on both a simple 2-dimensional test example, and a non-trivial industrial case of painting a tractor fender. The resulting trajectory is also proven feasible to be executed by an industrial robot.
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| 3. |
- Salman, R., et al.
(författare)
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An industrially validated CMM inspection process with sequence constraints
- 2016
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Ingår i: Procedia CIRP. - : Elsevier BV. - 2212-8271. ; 44, s. 138-143
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Konferensbidrag (refereegranskat)abstract
- An efficient CMM inspection process implemented in industry gives significant productivity improvements. A key part of this improvement is the optimization of the inspection sequences. To ensure quality of the inspection the sequences are often constrained with respect to the order of the measurements. This gives rise to so called precedence constraints when modelling the inspection sequence as a variation of the travelling salesperson problem (TSP). Two heuristic solution approaches and a generic optimizing algorithm are considered. A generation based stochastic algorithm is found to reduce cycle time by as much as 12% in comparison to the currently used algorithm.
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