FKIE Message Filters
fkie_message_filters library is a replacement for the ROS
message_filters package. It is written in modern C++ and more type-safe than
the original version.
The data flow is modeled with a pipeline metaphor, where data always flows from a source to a sink. A filter is both source and sink for data, possibly with different data types. For integration with ROS, the library provides a number of subscribers and publishers which act as sources or sinks of the data flow.
fkie_message_filters library requires C++14 or better. Some filters
The filters are written to be as data agnostic as possible. Therefore, many filters can process arbitrary data types and are not restricted to ROS messages. A few filters need access to ROS header information, such as time stamp or TF frame identifier.
Technically, the pipeline processing is executed by nested calls to receive and send functions. The library is thread-safe and exception-safe, but you are expected to handle your own exceptions in your callbacks. Exceptions which propagate through the library will abort processing for the message that caused the exception, and if not caught eventually by a preceding filter in the pipeline, terminate the program.
Certain filters, such as the
Buffer or the
TfFilter, can interoperate with
ROS callback queues for convenient workload scheduling.
See the API documentation for more details.
Buffer: Store and forward data
CameraPublisher: Publish consumed data to a ROS camera topic
CameraSubscriber: Subscribe to a ROS camera topic as data provider
Combiner: Combine multiple sinks into a single source with one of the following policies:
ExactTime: Exactly matching time stamp
ApproximateTime: Approximately matching time stamp
Divider: Split source with multiple inputs into independent output sinks
ImagePublisher: Publish consumed data to a ROS image topic
ImageSubscriber: Subscribe to a ROS image topic as data provider
Publisher: Publish consumed data on a ROS topic
Selector: Choose an arbitrary set of inputs to be forwarded
Sequencer: Enforce correct temporal order
SimpleUserFilter: Simplified filter with user-defined callback function
Subscriber: Subscribe to a ROS topic as data provider
TfFilter: Wait for TF transformations for incoming messages
UserFilter: Generic filter with user-defined callback function
UserSource: Manually operated data source
While you are free to derive your own classes from the one of the base classes, most programs will want to register a custom callback function for their application logic.
Unlike the original
message_filters, which mixed custom callbacks
and filter chaining, this library keeps those concepts distinct. Therefore,
there are two dedicated filters,
SimpleUserFilter works almost like a regular ROS callback, but it
expects a boolean return value that determines if the data is passed on
to subsequent filters in the pipeline (if any), or if processing terminates.
You can use this type of filter to consume data at the end of the pipeline,
or if you want to remove invalid inputs before further processing occurs.
UserFilter is more generic and can be used if your filter
outputs differ from its inputs. You can implement pretty much any kind of
A third filter
UserSource is a simple data source which can be used as
callback in third-party code.