nabled-sim
Cross-crate orchestration for Physical AI workflows in the nabled stack.
nabled-sim composes domain crates (nabled-model, nabled-kinematics, nabled-dynamics,
nabled-control, nabled-sensor) and horizontal layers (nabled-ml::stats, optional
nabled-linalg::signal) without reimplementing their algorithms. Use it for validated
robot context, simulation steps, batch IK, closed-loop control, and estimation pipelines.
Install
[]
= "0.0.11"
Key modules
context:RobotContext— model validation and chain/dynamics extraction.sim: semi-implicit integration calling dynamics FK/FD.manipulation: batch IK and pose-driven workflows.control_loop: closed-loop control wiring.estimation: filter pipelines over sensor models.pipeline: higher-level workflow composition.
Crate graph
- Depends on: all Physical AI domain crates plus
nabled-core,nabled-linalg,nabled-ml. - Used by: facade
nabled(physical-ai),pynabled.physical_ai.
Optional features
blas,lapack-provider: forwarded across dependent crates.openblas-system,openblas-static,netlib-system,netlib-static,magma-system.signal: enablesnabled-linalg/signalfor filter/signal paths.
[]
= { = "0.0.11", = ["openblas-system", "signal"] }
Example
use DynamicsConfig;
use load_planar2r_json;
use RobotContext;
let fixture = load_planar2r_json?;
let model = fixture.?;
let chain = fixture.?;
let ctx = new;
ctx.validate?;
Docs
- API docs: https://docs.rs/nabled-sim
- Orchestrator design:
docs/PHYSICAL_AI_ORCHESTRATOR.md - Workspace repo: https://github.com/MontOpsInc/nabled
- Facade feature:
nabledwithphysical-ai