![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |
System Dependencies
Dependant Packages
Launch files
Messages
Services
Plugins
Recent questions tagged ftl_launcher at Robotics Stack Exchange
![]() |
ftl_launcher package from aws-deepracer-follow-the-leader-sample-project repoctrl_pkg deepracer_interfaces_pkg ftl_launcher ftl_navigation_pkg object_detection_pkg webserver_pkg |
ROS Distro
|
Package Summary
Tags | No category tags. |
Version | 0.0.1 |
License | Apache 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Description | Learn to deploy an object detection model that enables the AWS DeepRacer device to identify and follow an object. |
Checkout URI | https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2022-06-06 |
Dev Status | UNKNOWN |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (-)
Good First Issues (-) Pull Requests to Review (-) |
Package Description
Additional Links
Maintainers
- AWS DeepRacer
Authors
AWS DeepRacer Follow the Leader (FTL) launcher package
Overview
The AWS DeepRacer Follow the Leader (FTL) sample project is an sample application built on top of the existing AWS DeepRacer application, which uses an object-detection machine learning model through which the AWS DeepRacer device can identify and follow a person. For information, see Getting Started.
License
The source code is released under Apache 2.0.
Installation
Follow these steps to install the AWS DeepRacer Follow the Leader (FTL) launcher package.
Prerequisites
The AWS DeepRacer device comes with all the prerequisite packages and libraries installed to run the FTL sample project. For more information about the preinstalled set of packages and libraries on the AWS DeepRacer, and about installing the required build systems, see Getting started. The FTL sample project requires the AWS DeepRacer application to be installed on the device, because it leverages most of the packages from the core application.
The following are the additional software and hardware requirements to get the FTL sample project to work on the AWS DeepRacer device.
-
Download and optimize the object-detection model: Follow the instructions to download and optimize the object-detection model and copy it to the required location on the AWS DeepRacer device.
-
Calibrate the AWS DeepRacer (optional): Follow the instructions to calibrate the mechanics of your AWS DeepRacer vehicle so the vehicle performance is optimal and it behaves as expected.
-
Set up the Intel Neural Compute Stick 2 (optional): The
object_detection_node
provides functionality to offload the inference to a Intel Neural Compute Stick 2 connected to the AWS DeepRacer device. This is an optional setting that enhances the inference performance of the object-detection model. For more details about running inference on the Movidius NCS (Neural Compute Stick) with OpenVINO™ toolkit, see this video.
Attach the Neural Compute Stick 2 firmly in the back slot of the AWS DeepRacer, open a terminal, and run the following commands as the root user to install the dependencies of the Intel Neural Compute Stick 2 on the AWS DeepRacer device.
-
Switch to the root user:
sudo su
-
Navigate to the OpenVino installation directory:
cd /opt/intel/openvino_2021/install_dependencies
-
Set the environment variables required to run the Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Run the dependency installation script for the Intel Neural Compute Stick:
./install_NCS_udev_rules.sh
Downloading and Building
Open a terminal on the AWS DeepRacer device and run the following commands as the root user.
-
Switch to the root user before you source the ROS 2 installation:
sudo su
-
Stop the
deepracer-core.service
that is currently running on the device:systemctl stop deepracer-core
-
Source the ROS 2 Foxy setup bash script:
source /opt/ros/foxy/setup.bash
-
Set the environment variables required to run Intel OpenVino scripts:
source /opt/intel/openvino_2021/bin/setupvars.sh
-
Create a workspace directory for the package:
mkdir -p ~/deepracer_ws cd ~/deepracer_ws
-
Clone the entire FTL sample project on the AWS DeepRacer device:
git clone https://github.com/aws-deepracer/aws-deepracer-follow-the-leader-sample-project.git cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/
-
Clone the
async_web_server_cpp
,web_video_server
, andrplidar_ros
dependency packages on the AWS DeepRacer device:cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && ./install_dependencies.sh
-
Fetch the unreleased dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ rosws update
-
Resolve the dependencies:
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && rosdep install -i --from-path . --rosdistro foxy -y
-
Build the packages in the workspace
cd ~/deepracer_ws/aws-deepracer-follow-the-leader-sample-project/deepracer_follow_the_leader_ws/ && colcon build
Using the FTL sample application
Follow this procedure to use the FTL sample application.
Running the node
To launch the FTL sample application as the root user on the AWS DeepRacer device, open another terminal on the device and run the following commands as the root user.
- Switch to the root user before you source the ROS 2 installation:
File truncated at 100 lines see the full file
Package Dependencies
Deps | Name |
---|---|
ament_cmake | |
ament_lint_auto | |
ament_lint_common | |
camera_pkg | |
ctrl_pkg | |
deepracer_navigation_pkg | |
deepracer_systems_pkg | |
device_info_pkg | |
i2c_pkg | |
inference_pkg | |
model_optimizer_pkg | |
rplidar_ros | |
sensor_fusion_pkg | |
servo_pkg | |
status_led_pkg | |
usb_monitor_pkg | |
webserver_pkg | |
web_video_server |