A methodical interpretation of adaptive robotics: Study and reformulation

The recent development of industrial manufacturing and social services has witnessed a significant trend of automation and intelligentization due to the wide application of robots and the technology of (AI). While robots liberate humans from tedious and dangerous work in hazardous environments, AI simplifies the programming of robots by automatically inferring patterns and models from the interaction between the robots and the environment. Nevertheless, the application of robots and AI to more general manufacturing and social tasks is still limited by the lack of flexibility and adaptability to the changes in the task and the environment. Thus, a new concept, adaptive robotics, has been proposed to address the desire that an AI-powered robot should be able to properly reprogram itself to these changes without human intervention. Nevertheless, this concept is yet too abstract to provide any specific guidance to the development of robot programs. In this paper, we attempt to provide methodical redefinition and reformulation of adaptive robotics both in conceptual and mathematical manners based on the study of previous results. First of all, we introduce the essential motivation and the conceptual origination of adaptability of mechanical systems. Then, we review the previous literature and explore the related work of adaptive robotics. Based on this, we provide a uniform mathematical formulation of adaptive robotics based on adaptive and robust Markov-decision process (MDP). Through this work, we attempt to inspire the generic framework of adaptive robotics incorporating the existing immature paradigms, by which we are aiming at a clarified and well-defined context of adaptive robotics for future research on related domains.