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Documentation

Intel® Robotics Open Source Project (Intel® ROS Project) to enable the object detection, 2D location, 3D location and tracking with GPU or Intel® Movidius™ NCS optimized deep learning backend, and Intel® RealSense™ camera under ROS framework.

The relationship among ROS packages are: alt text

Installation Prerequisites

Software environment: Ubuntu 16.04 and ROS Kinetic software configuration. 3D camera ROS node. (e.g. Intel® RealSense™ Camera node).

Hardware environment: RGBD camera (e.g. Intel® RealSense™D400 serial cameras).

Packages

Package

Description

ros_object_analytics

Object Analytics ROS node is based on 3D camera and ros_opencl_caffe ROS nodes to provide object classification, detection, localization and tracking via sync-ed 2D and 3D result array.

ros_opencl_caffe

ROS node for object detection backend.

object_msgs

ROS package for object related message definitions.

ros_intel_movidius_ncs

ROS node for object categorization backend with Intel® Movidius™ NCS stick.

ros_object_map

ROS node to publish mark tag of objects based on information provided by ROS object analytics when building map.

ros_moving_object

ROS node to provide object motion information (like object velocity on x, y, z axis) based on information provided by ROS object analytics.

Report a Bug

Use above github projects to report bugs or submit feature requests.

Contributing to Intel ROS Project

The Intel® ROS Project is developed and distributed under Apache 2.0 license. Follow the general ROS Contribute process to submit your code.

Reference

1. Intel® RealSense™ 3D camera is recommended as camera input, and the ROS packages are:

librealsense2

Underlying library driver for communicating with Intel® RealSense™ camera.

realsense2_camera

ROS Intel® RealSense™ camera node for publishing camera data.

2. Intel® ROS2 packages are also provided, please check ROS2 Intel Projects for more details.


2018-06-18 22:57