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DTSTAMP:20260417T190052Z
LOCATION:West Building\, Rooms 118-120
DTSTART;TZID=America/Los_Angeles:20250814T140000
DTEND;TZID=America/Los_Angeles:20250814T153000
UID:siggraph_SIGGRAPH 2025_sess135@linklings.com
SUMMARY:Rigid Bodies & Contacts
DESCRIPTION:Painless Differentiable Rotation Dynamics\n\nThis work introdu
 ces a forward and differentiable rigid-body dynamics framework using Lie-a
 lgebra rotation derivatives. The approach offers simplified, compact deriv
 atives, improved conditioning, and higher efficiency compared to tradition
 al methods. Applications include fundamental rigid-body probl...\n\n\nMagí
  Romanyà (Universidad Rey Juan Carlos) and Miguel A. Otaduy (Universidad R
 ey Juan Carlos, Meta Reality Labs Research)\n---------------------\nOffset
  Geometric Contact\n\nWe introduce Offset Geometric Contact (OGC), a groun
 dbreaking method offering "penetration-free for free" simulations of codim
 ensional objects.  OGC efficiently constructs offset volumetric shapes to 
 ensure stable, artifact-free collisions. Leveraging parallel GPU computati
 ons, it delivers real-time...\n\n\nAnka H. Chen (University of Utah, NVIDI
 A); Jerry Hsu and Ziheng Liu (University of Utah); Miles Macklin (NVIDIA);
  and Yin Yang and Cem Yuksel (University of Utah)\n---------------------\n
 C5D: Sequential Continuous Convex Collision Detection Using Cone Casting\n
 \nWe propose a fast, single-threaded continuous collision detection (CCD) 
 algorithm for convex shapes under affine motion. By combining conservative
  advancement with a cone-casting approach, it avoids primitive-level overh
 ead and enables efficient integration into intersection-free simulation me
 thods ...\n\n\nXiaodi Yuan (University of California San Diego); Fanbo Xia
 ng (Hillbot Inc.); Yin Yang (University of Utah); and Hao Su (University o
 f California San Diego, Hillbot Inc.)\n---------------------\nPutting Rigi
 d Bodies to Rest\n\nWe identify stable orientations of any rigid shape, an
 d the probability that it will rest at these orientations if randomly drop
 ped on the ground. We use a differentiable inverse version of our method t
 o design and fabricate shapes with target resting behavior, such as dice w
 ith target, nonuniform p...\n\n\nHossein Baktash (Carnegie Mellon Universi
 ty), Nicholas Sharp (NVIDIA), Qingnan Zhou and Alec Jacobson (Adobe Resear
 ch), and Keenan Crane (Carnegie Mellon University)\n---------------------\
 nRigid Bodies & Contacts - Interactive Discussion\n\nAfter the summary pre
 sentations, attendees will participate in an interactive discussion. Outsi
 de the room will be a series of poster boards for authors to gather around
  with the audience. Authors are invited to bring any material related to t
 heir paper that could instigate further conversation such...\n\n----------
 -----------\nA Versatile Quaternion-Based Constrained Rigid Body Dynamics\
 n\nWe present an implicitly-integrated, quaternion-based constrained Rigid
  Body Dynamics (RBD) that guarantees satisfaction of kinematic constraints
 , unifying the solution strategy for complex mechanical systems with arbit
 rary kinematic structures, by navigating subspaces spanned by constraint f
 orces a...\n\n\nGuirec Maloisel, Ruben Grandia, Christian Schumacher, Espe
 n Knoop, and Moritz Bächer (Disney Research)\n---------------------\nGeome
 tric Contact Potential\n\nWe present a systematic derivation of a continuu
 m potential defined for smooth and piecewise smooth surfaces, by identifyi
 ng a set of natural requirements for contact potentials. Our potential is 
 formulated independently of surface discretization and addresses the short
 comings of existing potential-...\n\n\nZizhou Huang and Maxwell Paik (New 
 York University); Zachary Ferguson (Massachusetts Institute of Technology,
  CLO Virtual Fashion); and Daniele Panozzo and Denis Zorin (New York Unive
 rsity)\n\nInterest Area: Research & Education\n\nRecording: Livestreamed, 
 Not Livestreamed, Recorded, Not Recorded\n\nRegistration Category: Full Co
 nference, Virtual Access, Thursday\n\nSession Chair: Minchen Li (Carnegie 
 Mellon University, Genesis AI)
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