October 1, 2021


16:10 - 16:15 Forewords from the organizers
  Invited talks session
16:15 - 16:35 Michel L’Hour (Department for Underwater Archaeology of the French Ministry of Culture)
How robots can help archeologists to study the deep sea cultural heritage
16:35 - 16:55 Oussama Khatib (Stanford University)
The Era of Human-Robot Collaboration: Deep Sea Exploration
16:55 - 17:15 Cyrille Chaidron (Artéka)
Multi-spectral imaging and machine learning for detecting archeological sites
17:15 - 17:35 Martin Saska (Czech Technical University)
A system for documentation of historical monuments by a team of unmanned aerial vehicles
17:35 - 17:55 Franck Ruffier (Institute of Movement Science)
A Shape-Adjusted Tridimensional Reconstruction of Cultural Heritage Artifacts Using a Miniature Quadrotor
  Contributed talk session
17:55 - 18:05 R. Luxman, Y. Emilia-Castro, M. Nurit, A. Siatou, G. Le Goïc, L. Brambilla, C. Degrigny, F. Marzani, A. Mansouri

Multi-light acquisitions and modeling of cultural heritage objects are well-established techniques used in characterizing surface geometry. Current systems that are used to perform this kind of acquisition consist mainly of free-form or dome-based. Both types have diverse constraints in terms of reproducibility, limitations on the size of objects being acquired, speed, and portability. This paper presents a novel robotic arm-based system, as well as a Reflectance Transformation Imaging (RTI) associated framework, for the optimization of RTI data stitching in terms of acquired images and light positions. The proposed methodology allows robust automation and reproducibility of series of acquisitions of large or complex scenes in two-dimensional space while optimizing pixel resolution. This new system was tested on a 20th century relief print-plate consisting of a series of scenes, to properly document the technological and decorative characteristics of the surface. Preliminary results show that the methodology can provide multi-lighting conditions adjustable to the size and complexity of the examined surface, enhances the repeatability of acquisitions, and reduces acquisition time through automated processes, thus improving the constraints of the commonly used acquisition systems.

18:05 - 18:10 Conclusion words from the organizers












2021 IEEE/RSJ International Conference on Intelligent Robots and Systems
Prague, Czech Republic