1992
DOI: 10.1145/142920.134065
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An algorithm with linear complexity for interactive, physically-based modeling of large proteins

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Cited by 16 publications
(10 citation statements)
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“…[44], but departs from our focus on dynamic simulation. In the area of simulation, [45], [46] implemented recursive algorithms with [46] able to handle closed loops, [47] used a Lagrange multiplier approach for protein modeling, [48] proposed using impulses to treat collisions while inserting springs to model contact, and [7] used a mix of impulses, temporary joint constraints, and the method of [49] to model collision, contact and friction. [50], [51] proposed an O(n) method although it required loop decomposition, dealt with only a handful of rigid bodies, and presented no clear method for handling large numbers of unpredictable contact and collision events.…”
Section: Previous Workmentioning
confidence: 99%
“…[44], but departs from our focus on dynamic simulation. In the area of simulation, [45], [46] implemented recursive algorithms with [46] able to handle closed loops, [47] used a Lagrange multiplier approach for protein modeling, [48] proposed using impulses to treat collisions while inserting springs to model contact, and [7] used a mix of impulses, temporary joint constraints, and the method of [49] to model collision, contact and friction. [50], [51] proposed an O(n) method although it required loop decomposition, dealt with only a handful of rigid bodies, and presented no clear method for handling large numbers of unpredictable contact and collision events.…”
Section: Previous Workmentioning
confidence: 99%
“…In constraint dynamics simulation, two different methods are frequently used: the reduced coordinate method 10 and Lagrange multiplier method. 11,12 Although the reduced coordinate method can also be used, symbolic knowledge of the body-space to world-space mapping is required to parameterize the system's degree of freedom. 12 Our system is based on the Lagrange multiplier method.…”
Section: Constraint Dynamicsmentioning
confidence: 99%
“…Many numerical techniques can be used to solve the above equation. [11][12][13] Among them, Baraff's extension method 12 gives linear time solutions for usual constraint functions. However, this method requires complicated algorithms for auxiliary constraints, which can frequently occur in the case of virtual mobiles.…”
Section: Constraint Dynamicsmentioning
confidence: 99%
“…Figure 7 summarizes the steps in our iterative constrained minimization algorithm. This method is presented in Gill et al (1981, p. 227), and its relative merits are described in Surles (1992a). The multipliers and variables converge to a constrained local minimum (Hestenes, 1975).…”
Section: Unconstrained Minimizationmentioning
confidence: 99%