Cloud-based Active Disturbance Rejection Control for Industrial Robots

Briese, Clemens; Vick, Axel; Krüger, Jörg

doi:10.1109/etfa.2018.8502580

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…The use of Cloud services facilitates generic control instructions to the robot and stable operation [24]. For example, factory managers can easily have an overview of the position of different robots around the factory floor, or override autonomous roaming to involve more robots assigned within a certain group or to prioritize specific tasks.…”

Section: Cloud Servicesmentioning

confidence: 99%

Offloading SLAM for Indoor Mobile Robots with Edge-Fog-Cloud Computing

Sarker

Queralta

Gia

et al. 2019

2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)

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Indoor mobile robots are widely used in industrial environments such as large logistic warehouses. They are often in charge of collecting or sorting products. For such robots, computation-intensive operations account for a significant percentage of the total energy consumption and consequently affect battery life. Besides, in order to keep both the power consumption and hardware complexity low, simple micro-controllers or single-board computers are used as onboard local control units. This limits the computational capabilities of robots and consequently their performance. Offloading heavy computation to Cloud servers has been a widely used approach to solve this problem for cases where large amounts of sensor data such as real-time video feeds need to be analyzed. More recently, Fog and Edge computing are being leveraged for offloading tasks such as image processing and complex navigation algorithms involving non-linear mathematical operations. In this paper, we present a system architecture for offloading computationally expensive localization and mapping tasks to smart Edge gateways which use Fog services. We show how Edge computing brings computational capabilities of the Cloud to the robot environment without compromising operational reliability due to connection issues. Furthermore, we analyze the power consumption of a prototype robot vehicle in different modes and show how battery life can be significantly improved by moving the processing of data to the Edge layer.

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Section: Cloud Servicesmentioning

confidence: 99%

Offloading SLAM for Indoor Mobile Robots with Edge-Fog-Cloud Computing

Sarker

Queralta

Gia

et al. 2019

2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT)

View full text Add to dashboard Cite

show abstract

“…Instead of deriving a state-space model of the robot to be controlled, Briese et al [8] investigated the possibility of using a non-model-based control approach (modified Switching Active Disturbance Rejection Control) for cloud-service-based distributed robot control in a network with jitter. In experiments, they achieved stabilization of all six axes of their robot for cycle times up to 100 ms.…”

Section: Introductionmentioning

confidence: 99%