Route Planning for Robot Systems

Skutella, Martin; Welz, Wolfgang

doi:10.1007/978-3-642-20009-0_49

Cited by 11 publications

(5 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3. Collision-free routing is a research topic of wide practical interest; besides rail-bound transportation, applications like scheduling industrial robots [21,23] come to mind. In order to avoid collisions it is customary to block (parts of) trajectories for others for the whole time interval it in use by one robot, even if this is not required in practice.…”

Section: Introductionmentioning

confidence: 99%

Ship Traffic Optimization for the Kiel Canal

Lübbecke

Möhring

2019

Operations Research

View full text Add to dashboard Cite

We introduce, discuss, and solve a hard practical optimization problem which we call the ship traffic control problem (STCP). Since we plan bi-directional traffic, STCP relates to, and in fact generalizes train timetabling on single-track networks. The objective of finding quickest routes motivates the integration of recent algorithmic ideas from dynamic collision-free routing of automated guided vehicles. We offer a unified view of routing and scheduling which blends simultaneous (global) and sequential (local) solution approaches to allot scarce network resources to a fleet of vehicles in a collision-free manner. This leads us to construct a fast online heuristic. The STCP originates from the Kiel Canal which is the basis for the trade between the countries of the baltic area and the rest of the world. As traffic is projected to significantly increase, the canal is planned to be enlarged in a billion Euro project. Our work forms the mathematical and algorithmic basis for a tool to evaluate the different enlargement options. In view of computational experiments on real traffic data expert planners approved that our combinatorial algorithm is well-suited for this decision support. With the help of instance-dependent lower bounds we assess the quality of our solutions which significantly improves upon manual plans. We are confident that our ideas can be extended to other application areas like train timetabling and collision-free routing, also in more general networks.

show abstract

Section: Introductionmentioning

confidence: 99%

Ship Traffic Optimization for the Kiel Canal

Lübbecke

Möhring

2019

Operations Research

View full text Add to dashboard Cite

show abstract

“…Avoidance & Cycle Time Optimization Hicham Touzani 1,2 , Nicolas Séguy 1 , Hicham Hadj-Abdelkader 1 , Raúl Suárez 3 , Jan Rosell 3 , Leopold Palomo-Avellaneda 3 and Samia Bouchafa 1…”

Section: Efficient Industrial Solution For Robotic Task Sequencing Pr...mentioning

confidence: 99%

Efficient Industrial Solution for Robotic Task Sequencing Problem With Mutual Collision Avoidance & Cycle Time Optimization

Touzani

Séguy

Hadj-Abdelkader

et al. 2022

IEEE Robot. Autom. Lett.

View full text Add to dashboard Cite

“…The method is applied to a complete line composed of three stations with a total of ten robots. In [15], the Welding Cell Problem (WCP) is introduced, which is a variant of the minmax MTSP with conflicts. Here, the problem is to find routes for robots such that the tour time for each robot is within a predefined maximum time.…”

Section: Problem Description and Related Literaturementioning

confidence: 99%

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

Spensieri

Carlson

Ekstedt

et al. 2016

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

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.Note to Practitioners-This paper is motivated by the problem of planning robot operations in welding applications in the automotive industry. Here, a number of welding tasks have been introduced along the car body: the goal is to let the robots perform such tasks while minimizing the cycle time (or makespan). The main difficulties, from the manufacturing engineer perspective, lie in assigning the tasks to the robots, deciding the order and the timing of the operations, avoiding collisions between the robots and the environment, and among the robots themselves. We present in this work an iterative approach, consisting of two steps: first, sequences for the robot operations are computed in order to minimize the cycle time, while neglecting collisions among robots; then, given the assignment of tasks to robots, the operations are reordered and scheduled while avoiding conflicts among robots. Robot motions are also automatically computed to avoid collisions with the static environment. We show an optimal algorithm, for the first part, based on implicit enumeration (B&B) and introduce a novel suboptimal algorithm, for the second part, to synchronize the robots.These algorithms are iterated while fetching information about the problem that are hard to compute, thus following a lazy approach. Tests on problems adapted from the literature and from the automotive i...

show abstract

Route Planning for Robot Systems

Cited by 11 publications

References 3 publications

Ship Traffic Optimization for the Kiel Canal

Ship Traffic Optimization for the Kiel Canal

Efficient Industrial Solution for Robotic Task Sequencing Problem With Mutual Collision Avoidance & Cycle Time Optimization

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

Contact Info

Product

Resources

About