The increased research in the field of Artificial Intelligence (AI) has led to the development of numerous Autonomous systems (ASs) that are becoming increasingly prevalent in our daily lives. These include autonomous driving, chatbots, drones and robots working in factories. Despite their considerable potential, AS are confronted with substantial challenges pertaining to safety, reliability, ethical considerations and human trust. A critical aspect of AS research lies in the improvement of decision-making algorithms, which gives rise to trust issues with humans. The sheer breadth of potential areas and scopes necessitates the classification and organization of research studies to facilitate a more nuanced understanding of the field of AS. To this end, this paper aims to use a Systematic Mapping Study (SMS) to identify trends and potential research gaps in the area of Autonomous systems. A comprehensive academic database was systematically searched, yielding a total of 1009 papers. Following a rigorous application of inclusion and exclusion criteria, 155 papers were selected for further analysis. The results obtained demonstrate specific trends pertaining to the challenges under investigation and the scopes utilized in conjunction with their quality objectives. The study elucidates these trends and demonstrates the potential for future research to be conducted based on the identified research gaps. The mapping of extant research facilitates the identification of potential challenges and innovations in the field of AS by researchers.