A typical NURBS surface model has a large percentage of superfluous control points that significantly interfere with the design process. This paper presents an algorithm for eliminating such superfluous control points, producing a T-spline. The algorithm can remove substantially more control points than competing methods such as B-spline wavelet decomposition. The paper also presents a new T-spline local refinement algorithm and answers two fundamental open questions on T-spline theory.

A typical NURBS surface model has a large percentage of superfluous control points that significantly interfere with the design process. This paper presents an algorithm for eliminating such superfluous control points, producing a T-spline. The algorithm can remove substantially more control points than competing methods such as B-spline wavelet decomposition. The paper also presents a new T-spline local refinement algorithm and answers two fundamental open questions on T-spline theory.

The reconstruction of the 3D structure of a static env ironm ent is a p ow erful cap ab ility ap p licab le to rob ot nav ig ation. W e p resent a nov el ap p roach to d eterm ine the 3D p ositions of a sp arse set of p oints track ed b y a sm all autonom ous rob ot in a static env ironm ent. U sing noisy feature track ing and a roug h estim ate of the essential m atrix , our m ethod has a relativ ely low com p utational cost and runs at fram e rate (1 5 fp s) on a sm all F P G A -b ased rob ot p latform . The w ork ing im p lem entation d em onstrates the p ow er of F P G A hard w are/ softw are co-d esig n in sm all rob otics app lications. In ad d ition, w e d escrib e our im p lem entation of a real-tim e im ag e d eriv ativ e com p utation sy stem for use b y our v ision alg orithm . W e p resent results of using our m ethod to nav ig ate a test env ironm ent.