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MANTIS: UAV for Indoor Logistic Operations | IEEE Conference Publication | IEEE Xplore

MANTIS: UAV for Indoor Logistic Operations


Abstract:

This paper presents the Unmanned Aerial Vehicle (UAV) MANTIS, developed for indoor inventory management in large-scale warehouses. MANTIS integrates a visual odometry (VI...Show More
Notes: As originally submitted and published there was an error in this document. The authors subsequently provided the following text: "by RRP - Recovery and Resilience Plan and by the European Funds Next Generation EU, following NOTICE No.2022-C05i0101-02 - Mobilizing Agendas/Alliances for Reindustrialization". The original article PDF remains unchanged.

Abstract:

This paper presents the Unmanned Aerial Vehicle (UAV) MANTIS, developed for indoor inventory management in large-scale warehouses. MANTIS integrates a visual odometry (VIO) system for precise localization, thus allowing indoor navigation in complex environments. The mechanical design was optimized for stability and maneuverability in confined spaces, incorporating a lightweight frame and efficient propulsion system. The UAV is equipped with an array of sensors, including a 2D LiDAR, six cameras, and two IMUs, which ensures accurate data collection. The VIO system integrates visual data with inertial measurements to maintain robust, drift-free localization. A behavior tree (BT) framework is responsible for the UAV mission planner assigned to the vehicle, which can be flexible and adaptive in response to dynamic warehouse conditions. To validate the accuracy and reliability of the VIO system, we conducted a series of tests using an OptiTrack motion capture system as a ground truth reference. Comparative analysis between the VIO and OptiTrack data demonstrates the efficacy of the VIO system in maintaining accurate localization. The results prove MANTIS, with the required payload sensors, is a viable solution for efficient and autonomous inventory management.
Notes: As originally submitted and published there was an error in this document. The authors subsequently provided the following text: "by RRP - Recovery and Resilience Plan and by the European Funds Next Generation EU, following NOTICE No.2022-C05i0101-02 - Mobilizing Agendas/Alliances for Reindustrialization". The original article PDF remains unchanged.
Date of Conference: 06-08 November 2024
Date Added to IEEE Xplore: 23 December 2024
ISBN Information:
Conference Location: Madrid, Spain

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