9.9 3D Pose Estimation

Docker usage reference: Module 3.7 Docker

Isaac ROS 3D pose estimation official link: https://nvidia-isaac-ros.github.io/repositories_and_packages/isaac_ros_pose_estimation/isaac_ros_centerpose/index.html

Overview

Isaac ROS Pose Estimation includes three main ROS 2 packages for 6-DoF object pose workflows. The table below summarizes the differences between them.

Package	Novel object without retraining	TAO support	Relative speed	Relative quality	Best fit
`isaac_ros_foundationpose`	Yes	N/A	Fast	Best	Zero-shot pose estimation and tracking for unseen objects
`isaac_ros_dope`	No	No	Fastest	Good	Mature, lightweight pose estimation for known objects
`isaac_ros_centerpose`	No	Yes	Faster	Better	Known-object pose estimation with NVIDIA TAO training support

These packages use GPU to accelerate DNN reasoning to estimate the object's attitude. The sensor function can use output predictions to integrate with the corresponding depth, thus providing the 3D attitude and distance of the object for navigation or operation.

Quick Start

In order to simplify development, we mainly use Isaac ROS Dev Docker images and perform impact demonstrations on them. The demonstration does not require the installation of any camera device to simulate data streams from the camera by playing the rosbag file.

If you plan to run the workflow on real hardware or with a connected camera, refer to the official Isaac ROS documentation for supported camera setups.

Open a terminal, move into the workspace, and enter the Isaac ROS development container.

bash


cd ${ISAAC_ROS_WS}/src

cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
./scripts/run_dev.sh

Run the following launch command:

bash


ros2 launch isaac_ros_examples isaac_ros_examples.launch.py launch_fragments:=centerpose,centerpose_visualizer interface_specs_file:=${ISAAC_ROS_WS}/isaac_ros_assets/isaac_ros_centerpose/quickstart_interface_specs.json model_name:=centerpose_shoe model_repository_paths:=[${ISAAC_ROS_WS}/isaac_ros_assets/models]

Open a second terminal and enter the container.

bash


cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
./scripts/run_dev.sh

Run the following command:

bash


ros2 bag play -l ${ISAAC_ROS_WS}/isaac_ros_assets/isaac_ros_centerpose/quickstart.bag

View the Result

Open the third terminal and enter the container.

bash


cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
./scripts/run_dev.sh

Run the following command to view the result:

bash


ros2 run rqt_image_view rqt_image_view /centerpose/image_visualized