Journal of Intelligent and Robotic Systems
Special Issue on: “Visual Perception for Micro Aerial Robots”
---- Introduction
During the last decades, aerial robots have emerged from a concept to a leading-edge technology with the enormous potential to become a valuable tool in multiple applications, in terms of human life safety and task execution efficiency. So far, the commercial use of aerial robots is mainly restricted within the photography-filming industry, but its growth is rapid, investing nowadays in applications that require autonomous inspection and environmental interaction. The vision of integrating aerial robotic platforms in the industrial process is in its infancy, with quite a few open challenges remaining. One of the backbone functionalities that these platforms should possess to enable and support such tasks are advanced perception capabilities. Specifically, from a scientific point of view, reliable localization, navigation, mapping and object perception are topics that have received a lot of attention, but still require further developments to reify aerial robot autonomous inspection and physical interaction.
---- Thematic Scope
The purpose of this special issue is to address theoretical and application-oriented problems in the general area of visual perception for micro-aerial robots and to identify and provide key perception solutions that meet the real-time constraints posed by aerial vehicles, following recent advances in computer vision and robotics. Topics of interest include (but are not limited to):
· Vision-based control and visual servoing
· Visual navigation, mapping, and SLAM
· Cooperative perception using multiple platforms
· Vision-assisted floating-base manipulation
· Deep Learning for visual perception
· Object recognition, tracking, semantic and 3D vision techniques
· Fusion of vision with other sensing systems, e.g., laser scanner
· Advanced visual sensors and mechanisms (event-based, solid state sensors, LiDAR, RGB-D, time-of-flight cameras, etc.)
· Aerial robot applications on key enabling perception technologies
· Model predictive control for vision-based autonomous navigation
· Reinforcement learning for visual perception
---- Manuscript Submission
Manuscripts should describe original and previously unpublished results which are currently not considered for publication in any other journal. All the manuscripts shall be submitted electronically athttp://www.editorialmanager.com/jint/, and will undergo a peer-review process.