There is a need for a node that will interface with a smartmicro radar driver and publish the data acquired by the sensor through the ROS2 pipeline. This package implements such a node.
./smart_extract.shros2 launch umrr_ros2_driver radar.launch.py
- ROS2 foxy
A smartmicro UMRR96 radar, UMRR11 radar or both are required to run this node. This code is bundled with a version of Smart Access API. Please make sure the version used to publish the data is compatible with this version:
- Date of release:
June 02, 2022 - Smart Access Automotive version:
v1.1.0 - User interface version:
UMRR96 Type 153 AUTOMOTIVE v1.2.1 - User interface version:
UMRR11 Type 132 AUTOMOTIVE v1.1.1
To add targets to the point cloud in a safe and quick fashion a
point_cloud_msg_wrapper library is used within
this project's node. This project can be installed either through rosdep or manually by executing:
sudo apt install ros-foxy-point-cloud-msg-wrapper
The inputs are coming as network packages generated in either of the following two ways:
- Through directly interfacing with the sensor
- Through a provided pcap file
These inputs are processed through the Smart Access C++ API and trigger a callback. Every time this callback is triggered a new point cloud message is created and published.
The driver publishes sensor_msgs::msg::PointCloud2 messages with the radar targets on the topic
umrr/targets which can be remapped through the parameters.
The node is configured through the parameters. Here is a short recap of the most important parts.
For more details, see the radar.template.yaml file.
client_id: the id of the client, must be a unique integerip: the IP of the used sensor or the sourceport: port to be used to receive the packetsiface_name: name of the used network interfaceframe_id: name of the frame in which the messages will be publishedhistory_size: size of history for the message publishermodel: the model of the sensor being used
The smartmicro radars come equipped with numerous features and modes of operation. Using the ros2 services provided one
may access these modes. A list of available sensor modes is given in the sensor_params.json.
A ros2 SetMode service should be called to implement these mode changes. There are three inputs to a ros2 service call:
param: name of the mode instruction (specific to the sensor)value: the mode of operation (specific to sensor where the modes are same)sensor_id: the id of the sensor to which the service call should be sent.
For instance, changing the Index of Transmit Antenna (tx_antenna_idx) of a UMRR-11 sensor to AEB (2) mode would require the following call:
ros2 service call /smartmicro_radar_node/set_radar_mode umrr_ros2_msgs/srv/SetMode "{param: "tx_antenna_idx", value: 2, sensor_id: 100}"
In order to use multiple sensors (maximum of up to ten sensors) with the node the sensors should be configured separately. The IP addresses of the sensors could be assigned using:
- The smartmicro tool
DriveRecorder. - Using the
Smart Access C++ API - Using
Sensor Servicesprovided by the node
Each sensor has to be assigned a unique IP address!
To use the ros2 SetIpservice we require two inputs:
value_ip: the value of the ip address in decimal. For instance to set the IP to192.168.11.64its corresponding value in decimal3232238400should be used.sensor_id: the sensor whose ip address is to be changed.
The call for such a service would be as follows:
ros2 service call /smartmicro_radar_node/set_ip_address umrr_ros2_msgs/srv/SetIp "{value_ip: 3232238400, sensor_id: 100}"
Note: For successfull execution of this call it is important that the sensor is restarted, the ip address in the
radar.template.yaml is updated and the driver is build again.
The sensor services respond with certain value codes. The following is a lookup table for the possible responses:
| Value | Description |
|---|---|
| 0 | No instruction Response |
| 1 | Instruction Response was processed successfully |
| 2 | General error |
| 6 | Invalid protection |
| 7 | Value out of minimal bounds |
| 8 | Value out of maximal bounds |
The dockerfile can be used to build and test the ros driver.
Accept the agreement and get the smartaccess release
./smart_extract.shBuilding docker container
docker build . -t umrr-ros:latestBuilding the driver with the docker container
docker run --rm -v`pwd`:/code umrr-ros colcon build --packages-select umrr_ros2_driver umrr_ros2_msgsRunning the unit and integration tests via the docker compose
docker-compose upGetting the test coverage via the docker container
docker run --rm -v`pwd`:/code umrr-ros colcon test-result --all --verboseStop and remove docker containers and networks
docker-compose downThe Smart Access release which will be downloaded using the script also offers platform support for armv8. In order to build the driver on an armv8 machine, the CMakeLists.txt should be adopted.
Instead of using the default lib-linux-x86_64_gcc_9 the user should plugin the lib-linux-armv8-gcc_9 for armv8.
This project is a joint effort between smartmicro and Apex.AI. The initial version of the code was developed by Igor Bogoslavskyi of Apex.AI (@niosus) and was thereafter adapted and extended by smartmicro.
Licensed under the Apache 2.0 License.