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This paper proposes a Priority-driven Accelerator Access Management (PAAM) framework for multi-process robotic applications built on top of the Robot Operating System (ROS) 2 middleware platform. The framework addresses the issue of predictable execution of time- and safety-critical callback chains that require hardware accelerators such as GPUs and TPUs. PAAM provides a standalone ROS executor that acts as an accelerator resource server, arbitrating accelerator access requests from all other callbacks at the application layer. This approach enables coordinated and priority-driven accelerator access management in multi-process robotic systems. The framework design is directly applicable to all types of accelerators and enables granular control over how specific chains access accelerators, making it possible to achieve predictable real-time support for accelerators used by safety-critical callback chains without making changes to underlying accelerator device drivers. The paper shows that PAAM also offers a theoretical analysis that can upper bound the worst-case response time of safety-critical callback chains that necessitate accelerator access. This paper also demonstrates that complex robotic systems with extensive accelerator usage that are integrated with PAAM may achieve up to a 91% reduction in end-to-end response time of their critical callback chains.
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This content will become publicly available on June 19, 2026
ROSCallBaX: Statically Detecting Inconsistencies in Callback Function Setup of Robotic Systems
Increasingly popular Robot Operating System (ROS) framework allows building robotic systems by integrating newly developed and/or reused modules, where the modules can use different versions of the framework (e.g., ROS1 or ROS2) and programming language (e.g. C++ or Python). The majority of such robotic systems' work happens in callbacks. The framework provides various elements for initializing callbacks and for setting up the execution of callbacks. It is the responsibility of developers to compose callbacks and their execution setup elements, and hence can lead to inconsistencies related to the setup of callback execution due to developer's incomplete knowledge of the semantics of elements in various versions of the framework. Some of these inconsistencies do not throw errors at runtime, making their detection difficult for developers. We propose a static approach to detecting such inconsistencies by extracting a static view of the composition of robotic system's callbacks and their execution setup, and then checking it against the composition conventions based on the elements' semantics. We evaluate our ROSCallBaX prototype on the dataset created from the posts on developer forums and ROS projects that are publicly available. The evaluation results show that our approach can detect real inconsistencies.
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- Award ID(s):
- 2416835
- PAR ID:
- 10637209
- Publisher / Repository:
- Association for Computing Machinery
- Date Published:
- Journal Name:
- Proceedings of the ACM on Software Engineering
- Volume:
- 2
- Issue:
- FSE
- ISSN:
- 2994-970X
- Page Range / eLocation ID:
- 668 to 689
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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