Abstract

Introduction Geometric problems arise in many areas. Computer graphics, robotics, manufacturing, and geographic information systems are some examples. Often the same geometric subproblems are to be solved. Hence a library providing solutions for core problems in geometric computing has a wide range of applications and can be very useful. The success of LEDA [16], a library of efficient data types and algorithms, has shown that the existence of a library can make a tremendous difference for taking advanced techniques in data structures and algorithms from theory to practice. The field of computational geometry is now very close to a state where it can provide such a library of geometric algorithms. Over the past twenty years many algorithms for geometric problems have been developed by computational geometers. Many of these algorithms clearly have no direct impact for geometric computing in practice, because they are efficient compared to other solutions only for huge problem i

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