A number of positzoning identification techniques have been used for mobile robots. Dead reckoning is a popular melhod, but zs not relzable when a robot trave h long distances or over an uneven surface because of uariations zn wheel diameter and wheel slzppage. The landmark method, which estzmates the current posiiion relaizae to landmarks, cannot be used an an unckarted cni:i.ronment. W e propose a new method called "Coopcrclti,ire Positioning wzth Multzple Robots." POT cooperai.ii:e positioning, we divide the robois into imo groups, .A and B. One group, say A , remains stationary and acts LIS a landmark while group B moves. The moving group R th.en slops and acts as a landmark for group .A. Thzs "dance" is repeated untd the target roboi p osition are reuch.ed. Cooperahoe positioning h,as a far lo.wer accumulated positzoning error than dead reckonzng, and can work in th.ree-dimenstons which i s noi possible with dead reckonzng. Also, this meth.od has rnherent landmarks and therefore works zn uncharted environments. This paper discusses the positioning acc'uraq of our meth.od wzth error variances ~O T an example milh three mobale robots.
This paper presents an overview of our research project on digital preservation of cultural heritage objects and digital restoration of the original appearance of these objects. As an example of these objects, this project focuses on the preservation and restoration of the Great Buddhas. These are relatively large objects existing outdoors and providing various technical challenges. Geometric models of the great Buddhas are digitally achieved through a pipeline, consisting of acquiring data, aligning multiple range images, and merging these images. We have developed two alignment algorithms: a rapid simultaneous algorithm, based on graphics hardware, for quick data checking on site, and a parallel alignment algorithm, based on a PC cluster, for precise adjustment at the university. We have also designed a parallel voxel-based merging algorithm for connecting all aligned range images. On the geometric models created, we aligned texture images acquired from color cameras. We also developed two texture mapping methods. In an attempt to restore the original appearance of historical objects, we have synthesized several buildings and statues using scanned data and a literature survey with advice from experts.
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