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Requirements

Note

Due to USB connection speed issues, running the software inside a virtual machine environment is not supported.

Minimum

An internet connection is required at the start of each session to access the Slamcore software license.

To run Slamcore software, the required hardware and OS specifications are:

x64

NVIDIA Jetson Nano, TX2, Orin AGX, Xavier NX and AGX

OS

Ubuntu 18.04 or 20.04

JetPack >= 4.4.1 up to L4T 32.6.1 or JetPack 5.0.2

CPU

x64 (with AVX2)

6-core @1400MHz recommended (Power mode 2)

USB port

>3.0

Camera

RealSense D435i, RealSense D455, OAK-D S2 Fixed-Focus

Listed are the minimum and recommended processors, memory and storage to run each of our SDK tools and APIs.

Tool/API

Processor

Memory

Storage

Minimum

Recommended

Minimum

Recommended

Minimum

Recommended

Dataset Recording

x86 (i5) or Jetson Nano

x86 (i5) or Jetson Nano

2GB

4GB

16GB ¹

128GB ¹ SSD

VIO Mode ²

x86 (i5) or Jetson Nano

x86 (i5) or Jetson Xavier NX

2GB

8GB

16GB

16GB

SLAM Mode ²

x86 (i5) or Jetson Nano

x86 (i5) or Jetson Xavier NX

4GB

16GB

16GB

16GB

2.5D Mapping ³

x86 (i5) or Jetson Nano

x86 (i5) or Jetson Xavier NX

4GB

16GB

16GB

16GB

ROS 2 Example ²

x86 (i5) or Jetson Xavier NX

x86 (i5) or Jetson Xavier NX

8GB

16GB

16GB

128GB SSD

The table above assumes no other significant processes are consuming system resources.

[1] : Disk write speeds must be sufficient to meet requirements (see Recording Datasets)

[2] : Assuming SLAM running at 15 frames per second

[3] : Assuming both SLAM and 2.5D mapping running at 15 frames per second

ROS Wrappers

The Slamcore ROS Wrappers support

  • ROS1 Melodic on Ubuntu 18.04 or

  • ROS 2 Foxy or Galactic on Ubuntu 20.04 (locally installed, or with Slamcore’s ROS 2 Docker image)

ROS1 Visualisation

To run both SLAM and the ROS1 visualisations (RViz) on the same system requires additional resources, we have tested this on a machine with the following hardware specification:

  • Core i7-7700HQ CPU @ 2.80GHz

  • 16GB of RAM

It is possible and recommended to run SLAM and the ROS visualisations on separate, networked systems.

Recording Datasets

To record datasets they will need to be written to a drive capable of sustaining write speeds set out in the table below.

Write Speed (MB/s)

x64

NVIDIA Jetson Platforms

without depth

25

12.5

with depth

100

50