Abstract
Indoor navigation and vehicle tracking require special measurement techniques. The reference points and routes used by classic AGV (Automated Guided Vehicle) systems are usually buried under floor surface or painted directly on the floor, thus limiting the set of possible transportation paths. However, the indoor environment of an industrial warehouse is dynamic, the number and location of objects inside are subject to frequent changes and these changes might not be reflected in the map of the area. In such conditions, navigation according to the on-board instruments (dead-reckoning) could provide valuable information about the position and orientation of the vehicle. This paper reports test results from a smart sensor using a 6-axis MEMS IMU unit and a self-calibrating procedure for indoor vehicle orientation tracking. The smart sensor, integrated with information from wheel encoders can produce 2D position coordinates suitable for navigation. Original data processing algorithm, applied in the sensor, was developed by the authors as a part of the research project on mobile robotics.
Highlights
Indoor navigation is an important problem in modern manufacturing systems
In classic AGV applications, the transportation paths used by mobile units cannot be shared with the pedestrian traffic or human-operated machines, the space cannot be allocated to other tasks
The smart sensor proved to be a suitable solution for short-term incremental navigation of the mobile robot moving on an even, horizontal floor
Summary
Indoor navigation is an important problem in modern manufacturing systems. Automated transport systems that make use of self-guided vehicles, such as AGV (Automated Guided Vehicle), require a network of orientation points to navigate through the production floors and storage areas. In classic AGV systems, markings used for vehicle navigation are located just beneath the floor surface or painted (or attached) directly on the floor [1] Such systems have a number of limitations which include: poor path flexibility and scaling (expansion) properties, low resistance to wear and high maintenance costs [2]. A modern idea of industry automation, referred to as industry 4.0, favours small autonomous entities that are able to communicate, exchange data and co-operate with other actors [3] It resembles the idea of holons and holonic systems where real and virtual actors share resources and co-operate to complete a global task. The proposed solution, unlike continuous measurement systems [11], profits from the fact that data received while the vehicle is moving differs significantly from the stationary state and uses it for sensor recalibration (known as zero-velocity update [12])
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