An algorithm for safe navigation of mobile robots by a sensor network in dynamic cluttered industrial environments

Li, Hang; Savkin, Andrey V.

doi:10.1016/j.rcim.2018.05.008

Cited by 48 publications

(17 citation statements)

References 39 publications

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“…Through system integration, Kolberg and Zühlke (2015) offer a similar overview, but between suppliers and customers. At the autonomy level, a large number of authors use the potential of autonomous robots to move products between workstations, including Müller et al (2018) and Li and Savkin (2018). Although the literature presented here is limited, the research work related to transport robots with autonomy capability is very extensive.…”

Section: Just-in-timementioning

confidence: 99%

Impacts of Industry 4.0 technologies on Lean principles

Rosin

Forget

Lamouri

et al. 2019

International Journal of Production Research

335

205

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Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies. On the other hand, many companies have already partially or fully implemented principles and tools from the Lean management approach, which is also aimed at improving productivity. While the two approaches use very different strategies, they share some common principles. The objective of this article is to highlight the links between the principles and tools proposed by Industry 4.0 and those proposed by the Lean management approach, with a particular focus on how some of Industry 4.0's technologies are improving the implementation of Lean principles, depending on the technologies' capability levels. As such, this study aims to provide a characterisation of the impacts of Industry 4.0 technologies on Lean principles according to targeted capability levels. The results obtained show strong support for Industry 4.0 technologies for Just-in-time and Jidoka, but little or no support for waste reduction and People and Team work. There is, therefore, a clear need to pursue the deployment of Lean management while improving certain Lean principles using Industry 4.0 technologies.

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Section: Just-in-timementioning

confidence: 99%

Impacts of Industry 4.0 technologies on Lean principles

Rosin

Forget

Lamouri

et al. 2019

International Journal of Production Research

335

205

View full text Add to dashboard Cite

show abstract

“…Covering the robot's surfaces to prevent human contact [39] is another challenge. Camera systems require the most safety distance [40]. A speedier human worker means a wider safety gap.…”

Section: Attacking Node Termination For Human Securitymentioning

confidence: 99%

Reformist Framework for Improving Human Security for Mobile Robots in Industry 4.0

Rajawat

Bedi

Goyal

et al. 2021

Mobile Information Systems

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In this paper, the cooperation between human and robot companies plays a significant role in factories, contributing to greater productivity and efficiency. However, this development breaches established safety procedures when the workspaces are separated from the robot and the human being. These changes have been reflected in industrial robotic safety standards for the last 20 years. We have directed the expansion of a broad field of examination, which focuses on avoiding robotic humans’ effects and minimizing associated risks and consequences. The paper depicts an analysis of prominent safety systems projected and implemented in engineering robotic surroundings that contribute to safe, collective work between humans and robots. Besides, the current regulation has introduced a review and new concepts. The discussion includes multidisciplinary approaches such as estimating and evaluating human-robot collision injuries, mechanical equipment and software to minimize human-robot impacts, impact detection systems, and collision prevention strategies and minimizing their impact to proposed approach for Human Security with Mobile Robots in Industry 4.0 using SDN and CPS with GMM-GM machine learning model.

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“…To define an integer h greater than zero as the level of resolution, the MLFs is represented by M h LF and can be built according to Equation (5). In detail, the value of a cell ξ for M h LF is the maximum cell value of a square region in M 0 LF , where the top left corner of the square region is at ξ and its length equals 2 h − 1 which indicates the resolution at the level h. In fact, the size of the square region indicates the size of a sub-space during the BnB search.…”

Section: The Same Equationmentioning

confidence: 99%

“…Therefore, it is crucial to achieve an accurate and reliable localization for the mobile platform. Some works have been done for robot localization in industry environments [3]- [5]. In their implementation, 2D Lidar is the key sensor due to its high frequency, high accuracy, low cost and small data size.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Maps Enhanced Localization System for Mobile Manipulator in Harsh Manufacturing Workshop

Huang

Zhang

et al. 2020

IEEE Access

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With excellent mobility and flexibility, mobile manipulators have great potential for loading and unloading tasks of numerical control machine tools (CNC) in manufacturing workshops. However, because of the rough and oily ground, dynamic obstacles and the convex plate of a CNC, harsh manufacturing workshop poses a huge challenge to the localization system of an autonomous mobile manipulator. To address the above problem, this paper presents a hybrid maps enhanced localization system which mainly consists of a global localization method and a pose tracking method. Hybrid maps including hybrid grid map, multiresolution likelihood fields (MLFs) and hybrid point map are constructed to efficaciously model the harsh environment and to improve localization performance. Our global localization method employs the convex hull sampling to spares dense Lidar data and the MLFs based branch and bound (BnB) search to speed up global search. To achieve real-time localization reliably and accurately, our pose tracking method seamlessly combines the BnB search and the adaptive Monte Carlo localization, and the Iterative Closest Point (ICP) based scan matching using the hybrid point map is adopted for higher accuracy. In addition, a distance filter improved by unscented transform is integrated into the pose tracking process to mitigate the influence of dynamic obstacles. The developed localization system is evaluated through different experiments including two weeks of loading and unloading tasks in a real manufacturing scenario, resulting in superior localization performance.

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An algorithm for safe navigation of mobile robots by a sensor network in dynamic cluttered industrial environments

Cited by 48 publications

References 39 publications

Impacts of Industry 4.0 technologies on Lean principles

Impacts of Industry 4.0 technologies on Lean principles

Reformist Framework for Improving Human Security for Mobile Robots in Industry 4.0

Hybrid Maps Enhanced Localization System for Mobile Manipulator in Harsh Manufacturing Workshop

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