The content discusses the challenges of planning robot tasks in environments with varying navigation times. It introduces a methodology to maximize temporal robustness using Mixed-integer linear programming and Markov Decision Processes. The approach is validated through simulations of robotic tasks.
The study addresses the importance of temporal robustness in satisfying task requirements despite time shifts. It presents a detailed strategy synthesis under deterministic and uncertain navigation times, emphasizing scalability and efficiency. The experiments demonstrate the practical application of the proposed methodologies in real-world scenarios.
Key points include defining Metric Interval Temporal Logic (MITL) tasks, modeling navigation durations, encoding constraints for deterministic and stochastic systems, and optimizing strategies for maximizing temporal robustness. The study highlights the significance of adaptability in addressing uncertainties in robot task planning.
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by Alexis Linar... في arxiv.org 03-07-2024
https://arxiv.org/pdf/2403.03727.pdfاستفسارات أعمق