Matches in SemOpenAlex for { <https://semopenalex.org/work/W2415674436> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W2415674436 abstract "Hessian information speeds convergence substantially in motion optimization. The better the Hessian approximation the better the convergence. But how good is a given approximation theoretically? How much are we losing? This paper addresses that question and proves that for a particularly popular and empirically strong approximation known as the Gauss-Newton approximation, we actually lose very little--for a large class of highly expressive objective terms, the true Hessian actually limits to the Gauss-Newton Hessian quickly as the trajectory's time discretization becomes small. This result both motivates it's use and offers insight into computationally efficient design. For instance, traditional representations of kinetic energy exploit the generalized inertia matrix whose derivatives are usually difficult to compute. We introduce here a novel reformulation of rigid body kinetic energy designed explicitly for fast and accurate curvature calculation. Our theorem proves that the Gauss-Newton Hessian under this formulation efficiently captures the kinetic energy curvature, but requires only as much computation as a single evaluation of the traditional representation. Additionally, we introduce a technique that exploits these ideas implicitly using Cholesky decompositions for some cases when similar objective terms reformulations exist but may be difficult to find. Our experiments validate these findings and demonstrate their use on a real-world motion optimization system for high-dof motion generation." @default.
- W2415674436 created "2016-06-24" @default.
- W2415674436 creator A5017897684 @default.
- W2415674436 creator A5021676288 @default.
- W2415674436 creator A5029642293 @default.
- W2415674436 creator A5065672819 @default.
- W2415674436 date "2016-05-30" @default.
- W2415674436 modified "2023-09-27" @default.
- W2415674436 title "On the Fundamental Importance of Gauss-Newton in Motion Optimization." @default.
- W2415674436 cites W1536308292 @default.
- W2415674436 cites W1557324374 @default.
- W2415674436 cites W2019965290 @default.
- W2415674436 cites W2044060118 @default.
- W2415674436 cites W2107464055 @default.
- W2415674436 cites W2113265921 @default.
- W2415674436 cites W2167856595 @default.
- W2415674436 cites W2293883387 @default.
- W2415674436 cites W757502775 @default.
- W2415674436 hasPublicationYear "2016" @default.
- W2415674436 type Work @default.
- W2415674436 sameAs 2415674436 @default.
- W2415674436 citedByCount "0" @default.
- W2415674436 crossrefType "posted-content" @default.
- W2415674436 hasAuthorship W2415674436A5017897684 @default.
- W2415674436 hasAuthorship W2415674436A5021676288 @default.
- W2415674436 hasAuthorship W2415674436A5029642293 @default.
- W2415674436 hasAuthorship W2415674436A5065672819 @default.
- W2415674436 hasConcept C114954040 @default.
- W2415674436 hasConcept C121332964 @default.
- W2415674436 hasConcept C126255220 @default.
- W2415674436 hasConcept C134306372 @default.
- W2415674436 hasConcept C158622935 @default.
- W2415674436 hasConcept C162324750 @default.
- W2415674436 hasConcept C195065555 @default.
- W2415674436 hasConcept C203616005 @default.
- W2415674436 hasConcept C2524010 @default.
- W2415674436 hasConcept C2777303404 @default.
- W2415674436 hasConcept C28826006 @default.
- W2415674436 hasConcept C33923547 @default.
- W2415674436 hasConcept C41008148 @default.
- W2415674436 hasConcept C50522688 @default.
- W2415674436 hasConcept C62520636 @default.
- W2415674436 hasConcept C73000952 @default.
- W2415674436 hasConcept C85189116 @default.
- W2415674436 hasConceptScore W2415674436C114954040 @default.
- W2415674436 hasConceptScore W2415674436C121332964 @default.
- W2415674436 hasConceptScore W2415674436C126255220 @default.
- W2415674436 hasConceptScore W2415674436C134306372 @default.
- W2415674436 hasConceptScore W2415674436C158622935 @default.
- W2415674436 hasConceptScore W2415674436C162324750 @default.
- W2415674436 hasConceptScore W2415674436C195065555 @default.
- W2415674436 hasConceptScore W2415674436C203616005 @default.
- W2415674436 hasConceptScore W2415674436C2524010 @default.
- W2415674436 hasConceptScore W2415674436C2777303404 @default.
- W2415674436 hasConceptScore W2415674436C28826006 @default.
- W2415674436 hasConceptScore W2415674436C33923547 @default.
- W2415674436 hasConceptScore W2415674436C41008148 @default.
- W2415674436 hasConceptScore W2415674436C50522688 @default.
- W2415674436 hasConceptScore W2415674436C62520636 @default.
- W2415674436 hasConceptScore W2415674436C73000952 @default.
- W2415674436 hasConceptScore W2415674436C85189116 @default.
- W2415674436 hasLocation W24156744361 @default.
- W2415674436 hasOpenAccess W2415674436 @default.
- W2415674436 hasPrimaryLocation W24156744361 @default.
- W2415674436 hasRelatedWork W1991214825 @default.
- W2415674436 hasRelatedWork W2006644442 @default.
- W2415674436 hasRelatedWork W2061404902 @default.
- W2415674436 hasRelatedWork W2286198664 @default.
- W2415674436 hasRelatedWork W2290964291 @default.
- W2415674436 hasRelatedWork W2583744849 @default.
- W2415674436 hasRelatedWork W2605181823 @default.
- W2415674436 hasRelatedWork W2610358195 @default.
- W2415674436 hasRelatedWork W2727389352 @default.
- W2415674436 hasRelatedWork W2739910069 @default.
- W2415674436 hasRelatedWork W2780878806 @default.
- W2415674436 hasRelatedWork W2895840764 @default.
- W2415674436 hasRelatedWork W2899698458 @default.
- W2415674436 hasRelatedWork W2971086474 @default.
- W2415674436 hasRelatedWork W3049469930 @default.
- W2415674436 hasRelatedWork W3090447637 @default.
- W2415674436 hasRelatedWork W3125318774 @default.
- W2415674436 hasRelatedWork W3147292290 @default.
- W2415674436 hasRelatedWork W3182143015 @default.
- W2415674436 hasRelatedWork W2137496927 @default.
- W2415674436 isParatext "false" @default.
- W2415674436 isRetracted "false" @default.
- W2415674436 magId "2415674436" @default.
- W2415674436 workType "article" @default.