RoboCompiler simplifies consistent robot modeling and control
RoboCompiler: Graph-Native Compilation of Closed-Chain Robots for Consistent Modeling, Control, and Simulation
Robotics
Summary
Robots with complex moving parts, like loops and linked joints, need precise models that work the same for controlling and simulating them. The authors created RoboCompiler, which turns a robot's mechanical setup into a shared model that keeps everything consistent across different uses. This approach speeds up calculations and keeps the robot's motions and forces accurate in simulations and real controls. The system was tested on real and simulated robots, showing it works well and reduces computational time significantly.
What this means in practice
- •For robot control engineers: Use RoboCompiler to create consistent robot models that integrate control and simulation, reducing errors and speeding up robot motion planning.
- •For robotics simulation developers: Integrate RoboCompiler in simulation platforms to improve accuracy and efficiency in modeling closed-chain and contact-rich robot dynamics.
Authors
Mehdi Heydari Shahna, Joongheon Kim, Jouni Mattila
Abstract
Robots with kinematic loops, coupled actuators, and changing contacts require consistent models of configuration, motion, force, and dynamics. Yet these interfaces are often reconstructed separately for control and simulation, making closure and actuation consistency difficult to maintain. This paper presents RoboCompiler, a graph-native framework that compiles a canonical mechanism graph into a shared mechanical interface. From bodies, joints, frames, inertias, and actuator ports, it constructs closure paths and analytic residual Jacobians, then assembles feasible configurations through rank-checked continuation and correction. A tangent lift maps independent velocities to full robot and task motion, while paired actuator-port maps preserve virtual work. A constraint-curvature correction extends the reduction to accelerations and projected rigid-body dynamics, including floating-base and support modes. Cycle-local evaluation, generated Jacobians, and dependency-aware reuse enable localized updates when closure inputs change. We evaluate physical loops and task-induced constraints on a Komatsu excavator, Unitree Go2, Franka Panda, Kangaroo, and a six-UPS Stewart platform. High-precision constrained-dynamics and independent Pinocchio checks confirm mechanical consistency; MuJoCo and Isaac Sim/PhysX executions demonstrate task performance and model reuse under native contact. For Kangaroo, compilation reduces residual-and-Jacobian evaluation time by 96.7% and closed-loop rollout wall time by 66.8%, with dynamics and control held fixed.