Optimal bid valuation using path finding for multi-robot task allocation

Öztürk, Savaş; Kuzucuoğlu, Ahmet Emin

doi:10.1007/s10845-014-0909-4

Cited by 22 publications

(12 citation statements)

References 41 publications

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“…In Group 2: Equations (8) and (9) are time constraints for each robot to perform the task, and each robot can wait more than one unit time in place; Equations (10) and (11) are the time connectivity constraint for each robot to perform tasks; Equations (12) and (13) guarantee that each robot can only perform one task per unit time.…”

Section: Variablementioning

confidence: 99%

“…Planning of multi-robot systems has two aspects: the first is task allocation, and the second is collision-free routing among multiple robots. There are several pieces of research on how to assign tasks in a multi-robot system to achieve the optimal utilization of resources [8]- [10]. However, the main problem of multi-robot systems is the conflict between multiple robots, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Routing of a Multi-Robot System Using a Time-Space Network Model

Meng

Xin

Peng

et al. 2019

2019 Chinese Automation Congress (CAC)

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In this paper, we study the collision-free routing of a multi-robot system to complete given tasks in the shortest time. In a robotic assembly unit, several stations work serially and in parallel. In a station, multiple robots share the same workspace and face the challenge of minimizing the cycle time and avoiding collisions at the same time. For this problem, we propose a new mathematical model that is the so-called timespace network (TSN) model. The TSN model can map the robot location constraints into the routing planning framework, leading a mixed integer programming problem. By solving this mixed integer programming problem, the collision-free path of multiple robots can be obtained. Finally, The simulation results illustrate the proposed TSN model can obtain the collision-free route of the multi-robot system.

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Section: Variablementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Routing of a Multi-Robot System Using a Time-Space Network Model

Meng

Xin

Peng

et al. 2019

2019 Chinese Automation Congress (CAC)

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“…Examples of such tasks are welding, cutting and plasma‐spraying on plates whose geometry cannot be known previously. Such processes are generally referred to as surface manufacturing [1]. In this work, damaged surface areas of hydroelectric turbine blades are to be reconstructed to its original profile when they have been damaged by a phenomenon known as cavitation, which produces cavities and flaws on the turbine blade surface.…”

Section: Introductionmentioning

confidence: 99%

Novel invariant feature descriptor and a pipeline for range image registration in robotic welding applications

Idrobo-Pizo

Motta

Borges³

2019

IET Image Processing

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“…In 2004, Lagoudakis et al used Prim Allocation [14] to generate the MSF (minimum spanning forest) of tasks for robots and then transformed the forest in paths by the depthfirst traversal. Later, some researchers [15,16] improved the depth-first traversal process in the prim allocation method and better results are obtained.…”

Section: Introductionmentioning

confidence: 99%

A Balanced Heuristic Mechanism for Multirobot Task Allocation of Intelligent Warehouses

Zhou

Shi

Wang

et al. 2014

Mathematical Problems in Engineering

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This paper presents a new mechanism for the multirobot task allocation problem in intelligent warehouses, where a team of mobile robots are expected to efficiently transport a number of given objects. We model the system with unknown task cost and the objective is twofold, that is, equally allocating the workload as well as minimizing the travel cost. A balanced heuristic mechanism (BHM) is proposed to achieve this goal. We raised two improved task allocation methods by applying this mechanism to the auction and clustering strategies, respectively. The results of simulated experiments demonstrate the success of the proposed approach regarding increasing the utilization of the robots as well as the efficiency of the whole warehouse system (by 5~15%). In addition, the influence of the coefficientαin the BHM is well-studied. Typically, this coefficient is set between 0.7~0.9 to achieve good system performance.

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Optimal bid valuation using path finding for multi-robot task allocation

Cited by 22 publications

References 41 publications

Routing of a Multi-Robot System Using a Time-Space Network Model

Routing of a Multi-Robot System Using a Time-Space Network Model

Novel invariant feature descriptor and a pipeline for range image registration in robotic welding applications

A Balanced Heuristic Mechanism for Multirobot Task Allocation of Intelligent Warehouses

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