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These wiki pages hold basic documentation on using the eRTIS device type and how to use the existing software packages on it.
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Current available guides:
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## eRTIS device
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An eRTIS (embedded Real Time Imaging Sonar) device is the sensor made by Cosys-Lab meant for applications in industrial environments where traditional sensing modalities such as LiDAR or cameras fail due to medium distortions. In these application scenarios, ultrasound can still retrieve high-resolution 3D object perception, allowing unencumbered sensing in challenging sensing scenarios.
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Our eRTIS device consists of a proprietary sonar hardware with a 32-element microphone
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array and a NVIDIA Jetson embedded GPU compute system. These systems work together to provide the user with the ability for both recording new measurements as well as (real time) processing of these recordings using our digital signal processing pipeline.
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you can learn a bit more about our sensors and find our publications here at [3Dsonar.eu](https://www.3dsonar.eu/).
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## Guides
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- [Initial Connection & Network Setup](https://cosysgit.uantwerpen.be/rtis-software/ertissoftwareusageguide/-/wikis/Initial-Connection-&-Network-Setup)
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- [RTIS Network Usage](https://cosysgit.uantwerpen.be/rtis-software/ertissoftwareusageguide/-/wikis/RTIS-Network-Usage)
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- [Developing Python with PyCharm](https://cosysgit.uantwerpen.be/rtis-software/ertissoftwareusageguide/-/wikis/Developing-Python-with-PyCharm) |
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- [Developing Python with PyCharm](https://cosysgit.uantwerpen.be/rtis-software/ertissoftwareusageguide/-/wikis/Developing-Python-with-PyCharm)
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## Software available
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The eRTIS device internally uses an NVIDIA Jetson embedded GPU compute system to fulfil all computing needs for both the sonar recordings or other applications. By default, we have prepared the Jetson default with some software packages to facilitate many possible applications and setups. Here is a short list of the most important packages:
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- Python 3.6 (with [RTIS Dev](https://cosysgit.uantwerpen.be/rtis-software/rtisdev/-/wikis/home), NumPy, SciPy, TensorFlow 2, Matplotlib, pandas, ...)
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- CUDA Toolkit
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- Docker
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- OpenCV
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- TensorRT
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- ROS
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- [RTIS Network Client](https://cosysgit.uantwerpen.be/rtis-software/rtisnetwork/-/wikis/home)
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