A Constraint-Based Approach for Hybrid Reasoning in
Robotics
av
Masoumeh Mansouri
Akademisk avhandling
Avhandling för filosofie doktorsexamen i Datavetenskap, som kommer att försvaras offentligt
fredag den 30 September 2016 kl. 13.15, Hörsal T, Örebro universitet, Örebro
Opponent: Dr. Nick Hawes, School of Computer Science University of Birmingham (UK)
Örebro universitet
Institutionen för Natur och Teknik 701 82 Örebro
Abstract
Masoumeh Mansouri (2016): A Constraint-Based Approach for Hybrid Reasoning in Robotics. Örebro Studies in Technology 69.
The quest of AI and Robotics researchers to realize fully AI-driven integrated robotic systems has not yet led to such realizations, in spite of great attainments in both research areas. This thesis claims that one of the major hindrances to these realizations is the lack of attention to what we call “the hybrid reasoning problem”. This is the problem of jointly reasoning about heterogeneous and inter-dependent aspects of the world, expressed in different forms and at different levels of abstraction.
In this thesis, we propose an approach to hybrid reasoning (or integrated reasoning) for robot applications. Our approach constitutes a systematic way of achieving a domain-specific integration of reasoning capabilities. Its underpinning is to jointly reason about the sub-problems of an overall hybrid problem in the combined search space of mutual decisions. Each sub-problem represents one viewpoint, or type of requirement, that is meaningful in the particular application. We propose a Constraint Satisfaction Problem (CSP) formulation of the hybrid reasoning problem. This CSP, called meta-CSP, captures the dependencies between sub-problems. It constitutes a high-level representation of the (hybrid) requirements that define a particular application. We formalize the meta-CSP in a way that is independent of the viewpoints that are relevant in the application, as is the algorithm used for solving the meta-CSP.
In order to verify the applicability of the meta-CSP approach in real-world robot applications, we instantiate it in several different domains, namely, a waiter robot, an automated industrial fleet management application, and a drill pattern planning problem in open-pit mining. These realizations highlight the important features of the approach, namely, modularity, generality, online reasoning and solution adjustment, and the ability to account for domain-specific metric and symbolic knowledge.
Keywords: Hybrid Knowledge Representation and Reasoning, Meta-CSP,
Robot Planning
Masoumeh Mansouri, School of Science and Technology
