DescriptionThesis title: "An Idiomatic Framework for Cognitive Robotics"
By increasingly taking over dull, dirty, and dangerous jobs, robots have demonstrated that they have the potential to transfigure the world we live in. However, the ability of robots to effectively deal with unpredictable and dynamic environments by learning and reasoning from experience is still relatively limited. This constitutes a major barrier to the development of robots that can integrate fully and seamlessly into human societies. The objective of this ph.d. study has been to aid roboticists in this development by designing a framework providing unifying standards for implementing artificial cognition for robots with characteristics of human cognition that can easily be shared and reused.
The main contribution of this ph.d. study is a proposal of a design for such a framework. The topic of this dissertation is the process undertaken to reach the proposed design, which has been structured through the design cycle. The properties of the framework are investigated in a series of papers describing different empirical studies considering both simulation-based and real-world single-case mechanism experiments. These empirical studies cover concepts related to the framework, such as real-time computation, distributed computations, multi-robot systems, low-level reactive attention mechanisms, and appraisal-driven decision mechanisms.
The results of these empirical studies are generalized into a design theory stating that the framework under given assumptions can provide implementations of artificial cognition for robots related to decision-making. The design theory further states several advantageous properties of using the framework for such implementations.
In the end, it is concluded that with this study important steps have been taken towards a framework providing unifying standards for implementing artificial cognition for robots.
|Period||14 Feb 2023|
|Examination held at|
|Degree of Recognition||International|