<i>RoboPlanner</i>: a pragmatic task planning framework for autonomous robots

Kattepur, Ajay; Purushotaman, Balamuralidhar

doi:10.1049/ccs.2019.0025

Cited by 12 publications

(4 citation statements)

References 21 publications

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“…Yetkin Ekren [109], Kattepur et al [110] Goods sensing and location awareness are elemental contributions of correct technology implementation in the warehouse. Zhao et al [111] Table 5.…”

Section: Practical Implications Publicationmentioning

confidence: 99%

Industrial Internet of Things (IIoT) and Other Industry 4.0 Technologies in Spare Parts Warehousing in the Oil and Gas Industry: A Systematic Literature Review

Khan,

Solvang,

2024

Logistics

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Background: Spare parts warehousing in the oil and gas industry is essential for offshore production. With the introduction of Industry 4.0 and its subsequent technological tools, new functions are enabled in industrial logistics activities. Efficiency, visibility, optimization, and productivity are often mentioned as benefits of successful Industry 4.0 technology implementation in logistics activities. In this paper, the implementation of Industry 4.0 technologies such as the Industrial Internet of Things (IIoT) in spare parts warehousing in the oil and gas industry is studied. Method: 133 peer-reviewed journal publications indexed in Scopus and Web of Science are analyzed in a systematic literature review. The review is structured as frequency and content analysis. Aim: As there is limited research on this specific topic, the aim is for this paper to be a theoretical foundation that assists the industry with future solutions. Results: The list of benefits of implementation gathered from the literature is comprehensive. However, the list of challenges is particularly pertinent to the oil and gas industry and indicates a strong inclination towards limited and controlled implementation of some technologies. The safety demands of the industry mean there are many limitations to implementation currently. Conclusions: This paper reflects on the results, identifies research gaps, and gives proposals for future research.

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“…Yetkin Ekren [109], Kattepur et al [110] Goods sensing and location awareness are elemental contributions of correct technology implementation in the warehouse. Zhao et al [111] Table 5.…”

Section: Practical Implications Publicationmentioning

confidence: 99%

Industrial Internet of Things (IIoT) and Other Industry 4.0 Technologies in Spare Parts Warehousing in the Oil and Gas Industry: A Systematic Literature Review

Khan,

Solvang,

2024

Logistics

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“…AI Planning is a model-based technology devoted to decision making, which can be used in a variety of application domains [37]. Roboplanner [38] is a framework that allows monitoring, state tracking and replanning/configuration of robotic plans using planning techniques. In other application domains, such as [39] and [40], AI planning is adopted to design a Web services composition system.…”

Section: Scaling Up Planiot In a Smart Spacementioning

confidence: 99%

PlanIoT: A Framework for Adaptive Data Flow Management in IoT-enhanced Spaces

Hassan

Bouloukakis

Kattepur³

et al. 2023

2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)

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This paper presents PlanIoT, a middleware approach for enabling adaptive data flow management in IoTenhanced spaces (e.g., buildings) using automated planning methodologies. Today's sensorized spaces deploy applications falling to diverse categories such as analytics, real-time, transactional, video streaming and emergency response. Depending on the category, applications have different QoS requirements related to timely delivery, networking resources, accuracy, etc. Typically, state-of-the-art data exchange systems introduce policies for bandwidth allocation or prioritization for specific data types and applications (e.g., camera data). PlanIoT introduces a generic QoS model to evaluate the performance of data flowing in Edge infrastructures and generates their performance metrics dataset. Such a dataset is used as input to automated planning representations to intelligently satisfy QoS requirements of deployed applications. The experimental results show that PlanIoT improves the end-to-end response time of time-sensitive flows by more than 50%, especially with an overloaded Edge infrastructure. We also show the adaptivity of our approach by considering emergency cases that require Edge infrastructure reconfiguration.

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“…Once the environment map has been constructed, the robot can use a path planning algorithm, such as A * [17] or RRT * [18], to generate a collision-free trajectory to reach the target location, even if there are obstacles [19,20]. With the development of deep learning, some work [21,22,23] built detailed semantic maps from images for complex indoor navigation learning in simulator [24,25,26].…”

Section: Related Workmentioning

confidence: 99%

Long-term object search using incremental scene graph updating

et al. 2022

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Effective searching for target objects in indoor scenes is essential for household robots to perform daily tasks. With the establishment of a precise map, the robot can navigate to a fixed static target. However, it is difficult for mobile robots to find movable objects like cups. To address this problem, we establish an object search framework that combines navigation map, semantic map, and scene graph. The robot updates the scene graph to achieve a long-term target search. Considering the different start positions of the robots, we weigh the distance the robot walks and the probability of finding objects to achieve global path planning. The robot can continuously update the scene graph in a dynamic environment to memorize the position relation of objects in the scene. This method has been realized in both simulation and real-world environments. The experimental results show the feasibility and effectiveness of this method.

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RoboPlanner: a pragmatic task planning framework for autonomous robots

Cited by 12 publications

References 21 publications

Industrial Internet of Things (IIoT) and Other Industry 4.0 Technologies in Spare Parts Warehousing in the Oil and Gas Industry: A Systematic Literature Review

Industrial Internet of Things (IIoT) and Other Industry 4.0 Technologies in Spare Parts Warehousing in the Oil and Gas Industry: A Systematic Literature Review

PlanIoT: A Framework for Adaptive Data Flow Management in IoT-enhanced Spaces

Long-term object search using incremental scene graph updating

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