Researchers Atef Azaiez and Alireza David Anisi have introduced a groundbreaking methodology to enhance the design of Robotic Autonomous Systems (RAS). Their work, focused on ensuring safety and reliability in RAS, leverages Probabilistic Model Checking (PMC) to systematically evaluate and analyze system design concepts, ultimately leading to verified designs.
The researchers emphasize the critical role of early hazard identification, risk assessment, and mitigation planning in the concept study phase of RAS development. This proactive approach lays a solid foundation for subsequent steps in the system engineering lifecycle. The complexity of RAS, coupled with the unpredictable and dynamic environments in which they operate, poses significant challenges not only for fault management and operational robustness but also for the selection of system design concepts.
Traditional approaches to addressing these challenges range from ad-hoc development and design practices to more systematic, statistical, and analytical techniques within Model Based Systems Engineering. Azaiez and Anisi propose a novel methodology that applies Probabilistic Model Checking (PMC) to enable a more rigorous and systematic evaluation of system design concepts. This method aims to produce a set of verified designs that meet stringent safety and reliability standards.
The researchers illustrate the application of their methodology using PRISM, a popular probabilistic model checker, in a practical use-case from agricultural robotics. This case study demonstrates how the proposed approach can be effectively applied to real-world scenarios, providing valuable insights into the design and verification process for RAS.
Furthermore, Azaiez and Anisi develop and present a domain-specific Design Evaluation Criteria for agricultural robotic systems (agri-RAS). This criteria serves as a guideline for evaluating and selecting the most appropriate design concepts, ensuring that the resulting systems are both efficient and reliable.
The implications of this research are significant for the maritime sector, where the deployment of autonomous systems is increasingly becoming a priority. By adopting the proposed methodology, maritime stakeholders can enhance the safety and reliability of their autonomous vessels, ensuring that they are well-equipped to navigate the complex and dynamic environments of the open seas. This approach not only mitigates risks but also optimizes the performance and operational robustness of maritime autonomous systems, paving the way for more efficient and sustainable maritime operations. Read the original research paper here.