Validation of a Time Based Routing Algorithm Using a Realistic Automatic Warehouse Scenario

Santos, Joana; Costa, Pedro; Rocha, Luís F.; Vivaldini, Kelen Cristiane Teixeira; Moreira, António Paulo; Veiga, Germano

doi:10.1007/978-3-319-27149-1_7

Cited by 11 publications

(12 citation statements)

References 8 publications

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“…To overcome the challenges related with the multi-AGV coordination problem, presented in the previous sections, in this section a new methodology for AGV's route planning is proposed. This novel methodology is called TEA* Algorithm [9,10], in which the paths are recalculated continuously, making it an online method. According to the vehicles' movements and the environment changes, TEA* updates the paths of each AGV in order to avoid collisions and to guarantee the continuous operation of the logistic system.…”

Section: Proposed Routing Algorithmmentioning

confidence: 99%

“…Bearing these ideas in mind, this paper proposes an integrated approach for both AGV route planning and task scheduling and dispatching. More in detail, the proposed routing algorithm called Time Enhanced A* (TEA*) is an extension of our previous work addressed in [9,10], that is, in this paper, further integrated with a scheduling module in order to minimize the tasks execution time. The main feature of TEA* is the addition of a temporal component to the known A* algorithm that generates routes efficiently, considering that each robot knows other robots' positions during the time.…”

Section: Introductionmentioning

confidence: 99%

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A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario

et al. 2021

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A multi-AGV based logistic system is typically associated with two fundamental problems, critical for its overall performance: the AGV’s route planning for collision and deadlock avoidance; and the task scheduling to determine which vehicle should transport which load. Several heuristic functions can be used according to the application. This paper proposes a time-based algorithm to dynamically control a fleet of Autonomous Guided Vehicles (AGVs) in an automatic warehouse scenario. Our approach includes a routing algorithm based on the A* heuristic search (TEA*—Time Enhanced A*) to generate free-collisions paths and a scheduling module to improve the results of the routing algorithm. These modules work cooperatively to provide an efficient task execution time considering as basis the routing algorithm information. Simulation experiments are presented using a typical industrial layout for 10 and 20 AGVs. Moreover, a comparison with an alternative approach from the state-of-the-art is also presented.

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Section: Proposed Routing Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario

et al. 2021

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“…It contains an additional component -time. This component allows a better prediction of the vehicles' movements during the run time [9].…”

Section: B Time Enhanced A*mentioning

confidence: 99%

“…This feature allows the algorithm to produce conflict free routes and, at the same time, deal with deadlock situations, since the paths are constantly recalculated and the map information is updated at each iteration. This way, the unpredictable events are considered in the input map, allowing to avoid the main challenges of any multi-robot approach, such as collisions and deadlocks [9]. Each node on the map has three dimensions: the Cartesian coordinates (x, y) and a representation of the discrete time.…”

Section: B Time Enhanced A*mentioning

confidence: 99%

A Survey on Path Planning Algorithms for Mobile Robots

Costa

Silva

2019

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

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The use of mobile robots is growing every day. Path planning algorithms are needed to allow the coordination of several robots, and make them travel with the least cost and without collisions. With this emerged the interest in studying some path planning algorithms, in order to better understand the operation of each one when applied in this type of robots. The objective of this paper is to present a state of the art survey of some algorithms of path planning for mobile robots. A brief introduction on mobile robots and trajectory planning algorithms is made. After, the basis of each algorithm is explained, their relative advantages and disadvantages are presented and are mentioned areas of application for each of them. This study was developed in order to implement some of these algorithms in the near future, with the objective to find out their relative advantages and disadvantages, and in which situations their implementation is more adequate.

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“…It is a path planning algorithm which resorts to a fixed graph to determine a trajectory based on the information of the 2D graph and the symbolic pose of each AGV (the edge each robot is occupying at the moment). A third dimension, Time, was added to enhance the information of the graph [12,13].…”

Section: Action Planning: Time Enhanced A* (Tea*) and Token Managermentioning

confidence: 99%

Development of an Autonomous Mobile Towing Vehicle for Logistic Tasks

Rocha

Sousa

Ferreira

et al. 2019

Advances in Intelligent Systems and Computing

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Frequently carrying high loads and performing repetitive tasks compromises the ergonomics of individuals, a recurrent scenario in hospital environments. In this paper, we design a logistic planner of a fleet of autonomous mobile robots for the automation of transporting trolleys around the hospital, which is independent of the space configuration, and robust to loss of network and deadlocks. Our robotic solution has an innovative gripping system capable of grasping and pulling nonmodified standard trolleys just by coupling a plate. Robots are able to navigate autonomously, to avoid obstacles assuring the safety of operators, to identify and dock a trolley, to access charging stations and elevators, and to communicate with the latter. An interface was built allowing users to command the robots through a web server. It is shown how the proposed methodology behaves in experiments conducted at the

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Validation of a Time Based Routing Algorithm Using a Realistic Automatic Warehouse Scenario

Cited by 11 publications

References 8 publications

A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario

A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario

A Survey on Path Planning Algorithms for Mobile Robots

Development of an Autonomous Mobile Towing Vehicle for Logistic Tasks

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