
רונן ברפמן
אקדמי בכיר
Plug'n Play Task-Level Autonomy for Robotics Using POMDPs and Probabilistic Programs
We describe AOS, the first general-purpose system for model-based control of autonomous robots using AI planning that fully supports partial observability and noisy sensing. The AOS provides a code-based language for specifying a generative model of the system, making model specification easier and model sampling efficient. It provides a language for specifying the relation between the model and the code, using which it auto-generates all required integration code. This allows Plug'n Play behavior, which facilitates incremental and modular system design. Extensive experiments on real and simulated robotic platforms demonstrate these advantages.
| שפת פרסום | אנגלית |
| דפים | 587-594 |
| כתב עת | IEEE Robotics and Automation Letters |
| כרך | 9 |
| נושא מספר | 1 |
| סטטוס פרסום | פורסם - 01.01.2024 |
Keywords
AI-enabled robotics
autonomous agents
integrated planning and control
planning under uncertainty
software architecture for robotic and automation
ASJC Scopus subject areas
Control and Systems Engineering
Biomedical Engineering
Human-Computer Interaction
Mechanical Engineering
Computer Vision and Pattern Recognition
Computer Science Applications
Control and Optimization
Artificial Intelligence