The complexity of humanoid robots is increasing with the availability of new sensors, embedded CPUs, and actuators. This wealth of technologies allows researchers to investigate new problems like multi-modal sensory fusion, whole-body control and multimodal human-robot interaction. Under the hood of these robots, the software architecture has an important role: it allows researchers to get access to the robot functionalities focusing primarily on their research problems and supports code reuse to minimize development and debugging, especially when new hardware becomes available. But more importantly, it allows increasing the complexity of the experiments that can be carried out before system integration becomes unmanageable, and debugging draws more resources than research itself. In this paper, we illustrate the software architecture of the iCub humanoid robot and the software engineering best practices that have emerged driven by the needs of our research community. We describe the latest development of the middleware supporting interface definition and automatic code generation, logging, ROS compatibility, and channel prioritization. We show the robot abstraction layer and how it has been modified to better address the requirements of the users and to support new hardware as it became available. We also describe the testing framework, and we have recently adopted for developing code using a test-driven methodology. We conclude the paper discussing the lessons we learned during the past 11 years of software development on the iCub humanoid robot.
REF summarize recent developments of the iCub's software architecture, including the compatibility with the Robot Operating System (ROS) and the introduction of a new testing framework.
The iCub Software Architecture: Evolution and Lessons Learned
Front. Robot. AI
Computer Science