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User:AarnavDhanuka/GSoC2022/Proposal
Project Title
Soft Bodies Simulation using Extended Position-Based Dynamics (XPBD)
Name
Aarnav Dhanuka
Contact
Email : [email protected]
LinkedIn : Aarnav Dhanuka | LinkedIn
Blender.chat : arcticblazer
Github : Aarnav Dhanuka | Github
Synopsis
We are surrounded by deformable objects that can't be accurately simulated in Blender yet. It is proposed in this project to build a new solver that would take as input a surface mesh and simulate the object as a soft body. The goal is to build a modular pipeline that will convert a surface mesh into a volumetric tetrahedral mesh using the "Incremental Delaunay Method" that will be passed to the "Extended Position-Based Dynamics (XPBD)" solver to simulate soft bodies.
Benefits
While for artists, this project will give the ability to simulate various deformable objects like muscles quickly and accurately, for developers, the project will introduce a remesher to convert surface meshes into tetrahedral volumetric meshes. In addition, it will add a new customizable solver system that will be used to simulate soft bodies and can also be used to simulate cloths in a significantly faster manner. The project will also allow for future development in physics simulations to write specific constraint functions for different cases.
Deliverables
The final product would be a general solver pipeline to perform soft-body simulations. This pipeline starts with a remesher to convert the input surface mesh to a volumetric tetrahedral mesh. This is followed by a general solver that can be invoked with various constraint functions specific to the object to be simulated. Constraint functions required to simulate cloths and softbodies, including distance, bending and volume constraints and collision control, would be implemented.
Project Details
Currently, soft bodies are simulated in Blender using cloth simulation, which is, in turn, implemented using various springs. To accurately simulate a cloth, the internal forces of the cloth are simulated using different types of springs, while the soft bodies are simulated by making stiff surface springs. This makes the old method complex and slow for cloth simulation since all forces need to be recalculated at each step, while the simulations are inaccurate for soft bodies.
The method proposed to be implemented, “XPBD: Position-Based Simulation of Compliant Constrained Dynamics” by Miles Macklin, Matthias M ̈uller and Nuttapong Chentanez[1], can act as a replacement to the current cloth solver and introduce a robust and fast Soft Body Solver.
As opposed to the force-based simulation, XPBD enforces hard constraints like length conservation between adjacent vertices (distance constraint) and tetrahedral volume conservation (volume constraint). These constraints are enforced by simply moving the vertices in the direction of the constraint solution. The method is very fast since this is done using first-order Euler integration. To quantify the model's accuracy, the authors simulated a chain with 20 particles falling under gravity and compared it to the analytic solution. They found that the error was under 6%, 2%, and 0.5% for 50, 100, and 1000 iterations respectively[1].
However, it must be noted that while the method is very accurate in a lot of cases, it is not as precise as the more complex methods like the Finite Element Method (FEM). However, the simulation speed is very fast, while the simulations are visually indistinguishable from the analytic solution. The authors displayed the method's speed by simulating various complex structures in real-time on a browser using just Javascript.
Soft body simulations require a volumetric tetrahedral. Thus, the surface mesh would need remeshing. A new internal data type would be created to store the vertices that make up each tetrahedral to store the volumetric information. To solve the task of remeshing, Incremental Delaunay Method[3] would be used, an iterative method that works by adding vertices iteratively to existing structures and dividing them.
XPBD is a constraint-based solver for which various constraints can be experimented with. For the scope of the project, the following constraints will be implemented:
1) Distance constraint (both) 2) Volume constraint (soft body) 3) Bending constraint (cloth) 4) Collision handling (both)
As a stretch goal, add UI controls to allow users to invoke the solver from the GUI.
Project Schedule
| Define new data types and write code to populate it | 2 weeks |
| Remeshing Algorithm | 3 weeks |
| XPBD Constraints: | |
| Distance Constraint and Bending Constraint | 1 week |
| Solid Volume Preservation | 3 days |
| Collision Handling | 2 weeks 2 days |
| Testing of all constraints together | 1 week |
| Stress testing | 1 week |
| Buffer | 1 week |
Schedule Conflicts - I will be graduating this summer, and I might have to start working at my new job in mid-August. To account for this, the majority of coding for the project has been scheduled for the initial weeks, while the later weeks have been kept for final testing.
Bio
I am a final semester student pursuing a double major in Physics and Computer Science from Birla Institute of Technology & Science, Pilani, India.
My fascination with Computer Graphics started when I first took it as an elective. This was followed by a project in medical imaging - "Segmentation of Retinal Vasculature of OCTA", to explore the domain in the context of medical imaging.
As part of the exploration for the project, I successfully implemented PBD for cloth simulation with distance constraints in Blender by tweaking the existing cloth data types[4].
References
1. https://matthias-research.github.io/pages/publications/XPBD.pdf
2. https://www.youtube.com/watch?v=uCaHXkS2cUg