Robot collaboration in warehouse

Pinkam, Nantawat; Bonnet, François; Chong, Nak Young

doi:10.1109/iccas.2016.7832331

Cited by 28 publications

(16 citation statements)

References 3 publications

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“…For this reason, most solution methods are approximate, i.e., they do not guarantee that solutions will have the minimum overall cost, but they are fast and provide solutions that are acceptable in practice. In this context, there are works that employ auction-based algorithms [25], heuristics [9,12,18], meta-heuristics [26,27,14] and hybrid algorithms [19,13,11], for example.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…The MRTA aims to ensure that the total cost of performing all tasks is minimized while minimizing the number of robots [9]. Another approach is to meet different constraints and complete one or more general objectives, which usually includes performing all tasks [10] and minimizing the makespan [11,12], traveled distance [9], or energy consumption [13,14].…”

mentioning

confidence: 99%

“…An efficient solution needs to consider constraints that can impact execution costs or increase problem complexity. Such constraints may include relocatable tasks ( [15,16]), deadline ([14, 12, 17, 18]), environment's uncertainties ( [19,17]) and different robots' properties such as load capacity ( [9,12]), traffic speed ( [11,16]) and energy consumption ( [13,14,12]). In smart warehouses, constraints still include the dispersion of robots, location and demand of the tasks, number of delivery stations, warehouse layout, and other environmental features such as obstacles, roadblocks, and other unpredictable situations.…”

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confidence: 99%

See 2 more Smart Citations

Efficient Task Allocation in Smart Warehouses with Multi-delivery Stations and Heterogeneous Robots

Oliveira¹,

Röning²,

Plentz³

et al. 2022

Preprint

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The task allocation problem in multi-robot systems (MRTA) is an NPhard problem whose viable solutions are usually found by heuristic algorithms. Considering the increasing need of improvement on logistics, the use of robots for increasing the efficiency of logistics warehouses is becoming a requirement. In a smart warehouse the main tasks consist of employing a fleet of automated picking and mobile robots that coordinate by picking up items from a set of orders from the shelves and dropping them at the delivery stations. Two aspects generally justify multi-robot task allocation complexity: (i) environmental aspects, such as multi-delivery stations and dispersed robots (since they remain in constant motion) and (ii) fleet heterogeneity, where robots' traffic speed and

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Section: Problem Descriptionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Efficient Task Allocation in Smart Warehouses with Multi-delivery Stations and Heterogeneous Robots

Oliveira¹,

Röning²,

Plentz³

et al. 2022

Preprint

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“…In Reference [25], a practical case of multi-robot navigation in warehouse has been discussed. The proposed work also deals with the positional uncertainty of robots and obstacles.…”

Section: Related Workmentioning

confidence: 99%

On Sharing Spatial Data with Uncertainty Integration Amongst Multiple Robots Having Different Maps

Ravankar

Hoshino

et al. 2019

Applied Sciences

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Information sharing is a powerful feature of multi-robot systems. Sharing information precisely and accurately is important and has many benefits. Particularly, smart information sharing can improve robot path planning. If a robot finds a new obstacle or blocked path, it can share this information with other remote robots allowing them to plan better paths. However, there are two problems with such information sharing. First, the maps of the robots may be different in nature (e.g., 2D grid-map, 3D semantic map, feature map etc.) as the sensors used by the robots for mapping and localization may be different. Even the maps generated using the same sensor (e.g., Lidar) can vary in scale or rotation and the sensors used might have different specifications like resolution or range. In such scenarios, the ‘correspondence problem’ in different maps is a critical bottleneck in information sharing. Second, the transience of the obstacles has to be considered while also considering the positional uncertainty of the new obstacles while sharing information. In our previous work, we proposed a ‘node-map’ with a confidence decay mechanism to solve this problem. However, the previous work had many limitations due to the decoupling of new obstacle’s positional uncertainty and confidence decay. Moreover, the previous work applied only to homogeneous maps. In addition, the previous model worked only with static obstacles in the environment. The current work extends our previous work in three main ways: (1) we extend the previous work by integrating positional uncertainty in the confidence decay mechanism and mathematically model the transience of newly added or removed obstacles and discuss its merits; (2) we extend the previous work by considering information sharing in heterogeneous maps build using different sensors; and (3) we consider dynamic obstacles like moving people in the environment and test the proposed method in complex scenarios. All the experiments are performed in real environments and with actual robots and results are discussed.

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“…However, in decentralized approaches [ 15 ] each robot calculates its path individually. Multi-robot navigation in warehouse has been discussed in [ 16 ]. Avoiding multi-robot path conflicts has been discussed in [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

Ravankar

Kobayashi

et al. 2017

Sensors

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Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments.

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Robot collaboration in warehouse

Cited by 28 publications

References 3 publications

Efficient Task Allocation in Smart Warehouses with Multi-delivery Stations and Heterogeneous Robots

Efficient Task Allocation in Smart Warehouses with Multi-delivery Stations and Heterogeneous Robots

On Sharing Spatial Data with Uncertainty Integration Amongst Multiple Robots Having Different Maps

Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

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