Linear solvers · Robotics
Conjugate Gradient (CG) for Robotics
Apply the conjugate gradient (cg) to real robotics problems — in the browser, with AI assistance.
CG minimizes the residual over expanding Krylov subspaces, converging far faster than stationary methods for SPD systems common in FEM.
In robotics, teams face challenges like contact dynamics, control stability, real-time performance. The conjugate gradient (cg) directly supports use cases such as rigid-body dynamics, control-loop tuning, actuator modeling, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical Robotics use cases
- Rigid-body dynamics
- Control-loop tuning
- Actuator modeling
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