Building a ROS-Based Testbed for Realistic Multi-Robot Simulation: Taking the Exploration as an Example

Yan, Zhi; Fabresse, Luc; Laval, Jannik; Bouraqadi, Noury

doi:10.3390/robotics6030021

Cited by 25 publications

(12 citation statements)

References 35 publications

(54 reference statements)

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“…However, there are only few and limited tools to support it. For instance, Yan in [14] presented a simulation tool based on a robot operating system (ROS).…”

Section: Robot Simulatorsmentioning

confidence: 99%

“…Each robot manufacturer has its own simulation environment for cell design and program testing, but the challenge arises when the same cell contains robots from different manufacturers working collaboratively with humans. Multiple robots can perform tasks in parallel, speed up the execution time, and improve system performance [14]. Thus, this work presents a novel methodology for process automation design, enhanced implementation, and real-time monitoring in operation.…”

Section: Introductionmentioning

confidence: 99%

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Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

et al. 2020

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Intelligent automation, including robotics, is one of the current trends in the manufacturing industry in the context of “Industry 4.0”, where cyber-physical systems control the production at automated or semi-automated factories. Robots are perfect substitutes for a skilled workforce for some repeatable, general, and strategically-important tasks. However, this transformation is not always feasible and immediate, since certain technologies do not provide the required degree of flexibility. The introduction of collaborative robots in the industry permits the combination of the advantages of manual and automated production. In some processes, it is necessary to incorporate robots from different manufacturers, thus the design of these multi-robot systems is crucial to guarantee the maximum quality and efficiency. In this context, this paper presents a novel methodology for process automation design, enhanced implementation, and real-time monitoring in operation based on creating a digital twin of the manufacturing process with an immersive virtual reality interface to be used as a virtual testbed before the physical implementation. Moreover, it can be efficiently used for operator training, real-time monitoring, and feasibility studies of future optimizations. It has been validated in a use case which provides a solution for an assembly manufacturing process.

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“…However, there are only few and limited tools to support it. For instance, Yan in [14] presented a simulation tool based on a robot operating system (ROS).…”

Section: Robot Simulatorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

et al. 2020

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“…The well supported ROS interface is provided by Gazebo thanks to the large community. Erlerobotics provides various simulation models (Yan et al, 2017) and has built an extended version of OpenAI Gym to combine it with Gazebo (Zamora et al, 2016).…”

Section: Simulationmentioning

confidence: 99%

Ai Motion Control – A Generic Approach to Develop Control Policies for Robotic Manipulation Tasks

Kurrek

Jocas

Zoghlami

et al. 2019

Proc. Int. Conf. Eng. Des.

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Current robotic solutions are able to manage specialized tasks, but they cannot perform intelligent actions which are based on experience. Autonomous robots that are able to succeed in complex environments like production plants need the ability to customize their capabilities. With the usage of artificial intelligence (AI) it is possible to train robot control policies without explicitly programming how to achieve desired goals. We introduce AI Motion Control (AIMC) a generic approach to develop control policies for diverse robots, environments and manipulation tasks. For safety reasons, but also to save investments and development time, motion control policies can first be trained in simulation and then transferred to real applications. This work uses the descriptive study I according to Blessing and Chakrabarti and is about the identification of this research gap. We combine latest motion control and reinforcement learning results and show the potential of AIMC for robotic technologies with industrial use cases.

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“…A testbed for robot software is one of the most promising applications [24,25] for robot middleware because its purpose does not require much portability. This kind of middleware usually provides bindings for multiple programming languages and simulators.…”

Section: Bottom-up Approachmentioning

confidence: 99%

Human-Error Prevention for Autonomous Edge Software Using Minimalistic Modern C++

Fukano

Ishikawa

2019

BDCC

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In science and engineering using edge-embedded software, it is necessary to demonstrate the validity of results; therefore, the software responsible for operating an edge system is required to guarantee its own validity. The aim of this study is to guarantee the validity of the sampled-time filter and time domain as fundamental elements of autonomous edge software. This requires the update law of a sampled-time filter to be invoked once per every control cycle, which we guaranteed by using the proposed domain specific language implemented by a metaprogramming design pattern in modern C++ (C++11 and later). The time-domain elements were extracted from the software, after which they were able to be injected into the extracted software independent from the execution environment of the software. The proposed approach was shown to be superior to conventional approaches that only rely on the attention of programmers to detect design defects. This shows that it is possible to guarantee the validity of edge software by using only a general embedded programming language such as modern C++ without auxiliary verification and validation toolchains.

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Building a ROS-Based Testbed for Realistic Multi-Robot Simulation: Taking the Exploration as an Example

Cited by 25 publications

References 35 publications

Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning

Ai Motion Control – A Generic Approach to Develop Control Policies for Robotic Manipulation Tasks

Human-Error Prevention for Autonomous Edge Software Using Minimalistic Modern C++

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