1. MIT AI Lab: B. Williams, H. Shrobe, R. Laddaga
Dynamic Domain Architectures for Model Based Autonomy
New Ideas
Controller
Plant
mode
identification
control
s’(t)
(t) f
s (t) g
o(t)
Model
Goals
Model-based
Deductive Executive
Executable Models with Explicit Constraints
Multiple domain specific languages for physical constituents and software components
Embedded in common base language, deductive framework
Integration of models via fast runtime deductive constraint resolution
Runtime compilation and optimization
Models preserved for diagnosis in case of breakdown
Three key services all model-driven:
Mode identification (diagnosis)
Reactive planning
Resource management
Impact
Schedule
Toolkit for embedded SW framework developers helps to capture & structure knowledge of the application domain.
Embedded frameworks can be integrated with each other.
Application programmers can implement and evolve application functionality at a high level, in concise, domain-appropriate, terms.
Application users obtain:
more functionality in a more timely fashion;
they can rely on the correctness and performance of the application as it continues to evolve.
Reactive Executive for Model-Based Autonomy milestones:
1: design of next-gen Livingstone; 2: implementation of next-gen Livingstone; 3: testing and evaluation of next-generation reactive executive.
Developers' Toolkit for Model-Based Autonomy milestones:
1: design meta-language describing DDA programs; 2: prototype DDA-based Application Generator; 3: test, evaluate DDA toolkit
Integration, Experimentation and Evaluation milestones:
1: prototype testbed application; 2: Application specific toolkits for testbed; 3:Reactive Executive for Model-Based Autonomy
MIT AI Lab: B. Williams, H. Shrobe, R. Laddaga