Developing a Framework for Semi-Autonomous Control

Abstract

Researchers and practitioners from the field of robotics and artificial intelligence (AI) have dedicated great effort to develop autonomous robotic system. The aim is to operate without any human assistance or intervention. In an unstructured and dynamic environment this is not readily achievable due to the high degree of complexity of perception and motion of the robots. For real-world applications, it is still desirable to have a human in the control loop for monitoring, detection of abnormalities and to intervene as necessary. In many critical operations full autonomy can be undesirable. Such tasks require human attributes of perception (e.g. judgment), reasoning and control to ensure reliable operations. Although, robots do not possess the these human attributes, it is possible for the current-state-of robots to perform useful tasks and to provide appropriate assistance to the human to correct his control input errors by supporting perception and cooperative task execution. Systems which facilitate cooperation between robots and human are becoming a reality and are attracting increasing attention from researchers. In the context of human-robot cooperation (HRC), one of the research concerns is the design and development of flexible system architecture for incorporating their strengths based on their complementary capabilities and limitations. A well-known paradigm to facilitate such cooperation is that via the concept of semi-autonomy. Although the concept of semi-autonomy is a widely adopted metaphor for developing human-robot system (HRS), there is no clear definition or agreement of how it should be represented. First, a formal representation of semi-autonomy is needed to identify and synthesise the key elements involved in the process of HRC. The purpose is to facilitate the development of a semi-autonomous control framework to seamless blend degree/level human control and robot autonomy at system-level. Second, there is a need to have a representation to address the role of semi-autonomy in decomposing and allocating tasks between humans and robots in a structured and systematic manner. This is essential in the initial design stage of HRS for providing a holistic basis of determining which system-level task should be performed by a human, by a robot or by a combination of both in accordance to their capabilities and limitations during task execution. A formalisation of semiautonomy to address how task can be allocated between humans and robots is lacking in the current literature of robotics. This is because applications of semi-autonomy are normally