fkie_message_filters repository

Repository Summary

Checkout URI https://github.com/fkie/message_filters.git
VCS Type git
VCS Version master
Last Updated 2018-12-07
Dev Status DEVELOPED
Released RELEASED

Packages

Name Version
fkie_message_filters 1.0.0

README

FKIE Message Filters

Summary

The 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.

Requirements

The fkie_message_filters library requires C++14 or better. Some filters depend on image_transport or tf2_ros.

Design

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.

Available Filters

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:
    • Fifo: First-In-First-Out
    • 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

Customized Filters

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, UserFilter and SimpleUserFilter, for callback processing.

The 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.

The UserFilter is more generic and can be used if your filter outputs differ from its inputs. You can implement pretty much any kind of transforming filter.

A third filter UserSource is a simple data source which can be used as callback in third-party code.