Abstract
The use of autonomous robots in areas that require executing a broad range of different tasks is currently hampered by the high complexity of the software that adapts the robot controller to different situations the robot would face. Current robot software frameworks facilitate implementing controllers for individual tasks with some variability, however, their possibilities for adapting the controllers at runtime are very limited and don’t scale with the requirements of a highly versatile autonomous robot. With the software presented in this paper, the behavior of robots is implemented modularly by composing individual controllers, between which it is possible to switch freely at runtime, since the required transitions are calculated automatically. Thereby the software developer is relieved of the task to manually implement and maintain the transitions between different operational modes of the robot, what largely reduces software complexity for larger amounts of different robot behaviors. The software is realized by a model-based development approach. We will present the metamodels enabling the modeling of the controllers as well as the runtime architecture for the management of the controllers on distributed computation hardware. Furthermore, this paper introduces an algorithm that calculates the transitions between two controllers. A series of technical experiments verifies the choice of the underlying middleware and the performance of online controller reconfiguration. A further experiment demonstrates the applicability of the approach to real robotics applications.
Highlights
Autonomous robotic systems, that are versatile in their application areas, will at some point face the problem that a change in control policy is needed in order to account for a new situation or task
To validate the choice of using Robot Construction Kit (Rock)/OrocosRTT, and the dynamic controller reconfiguration performance, various performance parameters of the system were measured in an experimental evaluation
In the real experiment, which will be presented in more detail in the subsection, we show, for example, a controller that implements an autonomous exploration behavior on a rover utilizing a LiDAR sensor for self-localization and mapping (SLAM) of the environment
Summary
Autonomous robotic systems, that are versatile in their application areas, will at some point face the problem that a change in control policy is needed in order to account for a new situation or task. The frameworks aim to achieve two main goals: On one hand, they simplify developing software components by providing tools or automatizing certain parts of the implementation, such as inter-process communication or. The amount of individual technology demonstrations is astonishing, but demonstrations of robots that can autonomously cope with a broad range of different situations are rarely shown We believe that this evolution of the robotics community is influenced by the current robotics software development frameworks, which are good tools for implementing static robot controllers for individual technology demonstrations, but provide little support for developing flexible control solutions as needed by highly versatile robots. To account for the high computational effort, especially of complex sensor processing routines, the controllers can be executed on distributed hardware This is an extension of the known component development frameworks. The last section concludes the work and discusses possible future work
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
