Demonstration of a Real-world Self-adaptive Robot Path-finding using Discrete Controller Synthesis
Jialong Li, Takuto Yamauchi, Nianyu Li, Zhengyin Chen, Mingyue Zhang, Takanori Hirano, Kenji Tei · 2023
This demo paper employs discrete controller synthesis (DCS) into a self-adaptive robot path-finding scenario with a real-world robot, to demonstrate the DCS-based self-adaptation underlying the principles of models@runtime and$D(\text{omain})\Vert S(\text{pecification})\models$R(equirement). Specifically, the demonstration centers around how DCS generates a new specification model$S^{\prime}$that adapts to a changed domain model$D^{\prime}$at runtime, entailing the satisfaction of the adjusted requirement model$R^{\prime}$. Demonstration Video: https://youtu.be/jFsGPpOdxic