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Abstract
Personal assistant robots provide novel technological solutions in order to monitor people’s activities, helping them in their daily lives. In this sense, unmanned aerial vehicles (UAVs) can also bring forward a present and future model of assistant robots. To develop aerial assistants, it is necessary to address the issue of autonomous navigation based on visual cues. Indeed, navigating autonomously is still a challenge in which computer vision technologies tend to play an outstanding role. Thus, the design of vision systems and algorithms for autonomous UAV navigation and flight control has become a prominent research field in the last few years. In this paper, a systematic mapping study is carried out in order to obtain a general view of this subject. The study provides an extensive analysis of papers that address computer vision as regards the following autonomous UAV vision-based tasks: (1) navigation, (2) control, (3) tracking or guidance, and (4) sense-and-avoid. The works considered in the mapping study—a total of 144 papers from an initial set of 2081—have been classified under the four categories above. Moreover, type of UAV, features of the vision systems employed and validation procedures are also analyzed. The results obtained make it possible to draw conclusions about the research focuses, which UAV platforms are mostly used in each category, which vision systems are most frequently employed, and which types of tests are usually performed to validate the proposed solutions. The results of this systematic mapping study demonstrate the scientific community’s growing interest in the development of vision-based solutions for autonomous UAVs. Moreover, they will make it possible to study the feasibility and characteristics of future UAVs taking the role of personal assistants.
Highlights
The use of unmanned aerial vehicles (UAVs) has significantly increased in recent years.These aircraft are mainly characterized by the fact that they allow access to remote places without the direct intervention of a human operator aboard
According to the classification and mapping process, a total of 144 papers have been published on computer vision for autonomous UAVs during the period studied
Number and Relevance of the Papers: (i) The number of research works focused on the use of computer vision for autonomous aerial vehicles has not stopped growing in recent years, which confirms the scientific community’s interest in this topic. (ii) More than 86% of the papers analyzed in this study were published in journals indexed in Journal Citation Reports (JCR) in such outstanding areas as Aerospace Engineering, Robotics, Automation, and Artificial Intelligence
Summary
The use of unmanned aerial vehicles (UAVs) has significantly increased in recent years. These aircraft are mainly characterized by the fact that they allow access to remote places without the direct intervention of a human operator aboard. An emerging domain is flying assistance robotics, where UAVs come through with a present and future model of fully autonomous personal monitoring capacities. Some examples are Aire, a self-flying robotic assistant for the home [2], Fleye, a personal flying robot [3], and CIMON and Astrobee, flying assistant robots in the space station [4,5]
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