Machine learning-based multi-sensor fusion for warehouse robot in GPS-denied environment

Singh, Abhilasha; Kalaichelvi, V.; Karthikeyan, R.

doi:10.1007/s11042-023-17753-0

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2024

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Cited by 2 publications

References 26 publications

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Design of rescue robot system based on multi-sensor information fusion

Zhao,

Zhang,

et al. 2024

Proceedings of the 2024 4th International Conference on Control and Intelligent Robotics

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Design of rescue robot system based on multi-sensor information fusion

Zhao,

Zhang,

et al. 2024

Proceedings of the 2024 4th International Conference on Control and Intelligent Robotics

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Indoor Positioning Systems in Logistics: A Review

Vaccari,

Coruzzolo,

Lolli

et al. 2024

Logistics

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Background: Indoor Positioning Systems (IPS) have gained increasing relevance in logistics, offering solutions for safety enhancement, intralogistics management, and material flow control across various environments such as industrial facilities, offices, hospitals, and supermarkets. This study aims to evaluate IPS technologies’ performance and applicability to guide practitioners in selecting systems suited to specific contexts. Methods: The study systematically reviews key IPS technologies, positioning methods, data types, filtering methods, and hybrid technologies, alongside real-world examples of IPS applications in various testing environments. Results: Our findings reveal that radio-based technologies, such as Radio Frequency Identification (RFID), Ultra-wideband (UWB), Wi-Fi, and Bluetooth (BLE), are the most commonly used, with UWB offering the highest accuracy in industrial settings. Geometric methods, particularly multilateration, proved to be the most effective for positioning and are supported by advanced filtering techniques like the Extended Kalman Filter and machine learning models such as Convolutional Neural Networks. Overall, hybrid approaches that integrate multiple technologies demonstrated enhanced accuracy and reliability, effectively mitigating environmental interferences and signal attenuation. Conclusions: The study provides valuable insights for logistics practitioners, emphasizing the importance of selecting IPS technologies suited to specific operational contexts, where precision and reliability are critical to operational success.

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Machine learning-based multi-sensor fusion for warehouse robot in GPS-denied environment

Cited by 2 publications

References 26 publications

Design of rescue robot system based on multi-sensor information fusion

Design of rescue robot system based on multi-sensor information fusion

Indoor Positioning Systems in Logistics: A Review

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