Autonomous Reality Modelling for Cultural Heritage Sites employing cooperative quadrupedal robots and unmanned aerial vehicles

Nowadays, the use of advanced sensors, such as terrestrial 3D laser scanners, mobile LiDARs and Unmanned Aerial Vehicles (UAV) photogrammetric imaging, has become the prevalent practice for 3D Reality Modeling and digitization of large-scale monuments of Cultural Heritage (CH). In practice, this process is heavily related to the expertise of the surveying team, handling the laborious planning and time-consuming execution of the 3D mapping process that is tailored to the specific requirements and constraints of each site. To minimize human intervention, this paper introduces a novel methodology for autonomous 3D Reality Modeling for CH monuments by employing au-tonomous biomimetic quadrupedal robotic agents and UAVs equipped with the appropriate sensors. These autonomous robotic agents carry out the 3D RM process in a systematic and repeatable ap-proach. The outcomes of this automated process may find applications in digital twin platforms, facilitating secure monitoring and management of cultural heritage sites and spaces, in both indoor and outdoor environments.

Multi-agent robotic systems and exploration algorithms: Applications for data collection in construction sites

The construction industry has been notoriously slow to adopt new technology and embrace automation. This has resulted in lower efficiency and productivity compared to other industries where automation has been widely adopted. However, recent advancements in robotics and artificial intelligence offer a potential solution to this problem. In this study, a methodology is proposed to integrate multi-robotic systems in construction projects with the aim of increasing efficiency and productivity. The proposed approach involves the use of multiple robot and human agents working collaboratively to complete a construction task. The methodology was tested through a case study that involved 3D digitization of a small, occluded space using two robots and one human agent. The results show that integrating multi-agent robotic systems in construction can effectively overcome challenges and complete tasks efficiently. The implications of this study suggest that multi-agent robotic systems could revolutionize the industry.

Relative Visual Localization for Unmanned Aerial Systems

Cooperative Unmanned Aerial Systems (UASs) in GPS-denied environments demand an accurate pose-localization system to ensure efficient operation. In this paper we present a novel visual relative localization system capable of monitoring a 360$^o$ Field-of-View (FoV) in the immediate surroundings of the UAS using a spherical camera. Collaborating UASs carry a set of fiducial markers which are detected by the camera-system. The spherical image is partitioned and rectified into a set of square images. An algorithm is proposed to select the number of images that balances the computational load while maintaining a minimum tracking-accuracy level. The developed system tracks UASs in the vicinity of the spherical camera and experimental studies using two UASs are offered to validate the performance of the relative visual localization against that of a motion capture system.