A Two-Stage Approach to Path Planning and Collision Avoidance of Multibridge Machining Systems

Li, Jun; Meng, Xianghu; Zhou, MengChu; Dai, Xianzhong

doi:10.1109/tsmc.2016.2531648

Cited by 31 publications

(9 citation statements)

References 79 publications

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“…Recently, a CTSP formulation has been given by Meng et al [18] in order to model and solve multibridge machine planning in the industry. A similar model has been used to model collision-free scheduling [19] and path-planning [20] in multibridge machining systems. Xu et al [21] developed the Delaunay-triangulation-based variable neighborhood search in order to solve large-scale CTSPs.…”

Section: Related Workmentioning

confidence: 99%

GMP: A Genetic Mission Planner for Heterogeneous Multirobot System Applications

Miloradović¹,

Çürüklü²,

Ekström³

et al. 2022

IEEE Trans. Cybern.

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The use of multiagent systems (MASs) in real-world applications keeps increasing, and diffuses into new domains, thanks to technological advances, increased acceptance, and demanding productivity requirements. Being able to automate the generation of mission plans for MASs is critical for managing complex missions in realistic settings. In addition, finding the right level of abstraction to represent any generic MAS mission is important for being able to provide general solution to the automated planning problem. In this article, we show how a mission for heterogeneous MASs can be cast as an extension of the traveling salesperson problem (TSP), and we propose a mixed-integer linear programming formulation. In order to solve this problem, a genetic mission planner (GMP), with a local plan refinement algorithm, is proposed. In addition, the comparative evaluation of CPLEX and GMP is presented in terms of timing and optimality of the obtained solutions. The algorithms are benchmarked on a proposed set of different problem instances. The results show that, in the presence of timing constraints, GMP outperforms CPLEX in the majority of test instances. Index Terms-Extended colored traveling salesperson problem (ECTSP), genetic algorithm (GA), multirobot mission planning, multirobot systems.

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Section: Related Workmentioning

confidence: 99%

GMP: A Genetic Mission Planner for Heterogeneous Multirobot System Applications

Miloradović¹,

Çürüklü²,

Ekström³

et al. 2022

IEEE Trans. Cybern.

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“…The following are some example approaches and applications for task sequencing and scheduling. In [16], path planning, job scheduling and collision avoidance of multibridge machining system are solved using a variation of the well-known traveling salesmen problem and population-based incremental learning. Han et al [17] developed algorithms for allocating asset packages to a set of interdependent tasks that are associated with resource requirements.…”

Section: Related Workmentioning

confidence: 99%

A Two-Stage Approach to Collaborative Fiber Placement through Coordination of Multiple Autonomous Industrial Robots

Hassan

Liu

2018

J Intell Robot Syst

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The use of multiple Autonomous Industrial Robots (AIRs) as opposed to a single AIR to perform fiber placement brings about many challenges which have not been addressed by researchers. These challenges include optimal division and allocation of the work and performing path planning in a coordinated manner while considering the requirements and constraints that are unique to the fiber placement task. To solve these challenges, a two-stage approach is proposed in this paper. The first stage considers multiple objectives to optimally allocate each AIR with surface areas, while the second stage aims to generate coordinated paths for the AIRs. Within each stage, mathematical models are developed with several unique objectives and constraints that are specific to the multi-AIR collaborative fiber placement. Several case studies are presented to validate the approach and the proposed mathematical models. Comparison studies using a different number of AIRs and variations of the developed mathematical models are also presented.

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“…Colors are used to characterize the cities' accessibility for salesmen and can be applied to some real-world scheduling problems in which the tasks to be performed own different accessibilities for movable processing devices [2]. Li and Meng apply the CTSP to schedule multibridge machining systems for avoiding collision [3,4]. In addition, He and Hao [5] propose a two-phase local search for solving the CTSP.…”

Section: Introductionmentioning

confidence: 99%

A Colored Traveling Salesman Problem with Varying City Colors

Meng

Zhou

2021

Discrete Dynamics in Nature and Society

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A colored traveling salesman problem (CTSP) is a path optimization problem in which colors are used to characterize diverse matching relationship between cities and salesmen. Namely, each salesman has a single color while every city has one to multiple salesmen’s colors, thus allowing salesmen to visit exactly once the cities of their colors. It is noteworthy that cities’ accessibilities to salesmen may change over time, which usually takes place in the multiwarehouse distribution of online retailers. This work presents a new CTSP with dynamically varying city colors for describing and modeling some scheduling problems with variable city accessibilities. The problem is more complicated than the previously proposed CTSP with varying edge weights. In particular, the solution feasibility changes as the cities change their colors, that is, a feasible original solution path may become no longer feasible after city colors change. A variable neighborhood search (VNS) algorithm is presented to solve the new problem. Specifically, a dynamic environment simulator with an adjustable frequency and amplitude is designed to mimic such color changes. Then, direct-route encoding, greedy initialization, and appropriate population immigrant are proposed to form an enhanced VNS, and then its performance is evaluated. The results of extensive experiments show that the proposed VNS can quickly track the environmental changes and effectively resolve the problem.

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A Two-Stage Approach to Path Planning and Collision Avoidance of Multibridge Machining Systems

Cited by 31 publications

References 79 publications

GMP: A Genetic Mission Planner for Heterogeneous Multirobot System Applications

GMP: A Genetic Mission Planner for Heterogeneous Multirobot System Applications

A Two-Stage Approach to Collaborative Fiber Placement through Coordination of Multiple Autonomous Industrial Robots

A Colored Traveling Salesman Problem with Varying City Colors

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