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CONTROL TOOLBOX
C++ library for robotics optimal control, estimation, and nonlinear MPC
BSD-2-Clause
ABOUT
Robotics labs often rewrite iLQR, multiple shooting, and constraint plumbing for every new plant. The Control Toolbox gives shared C++ models, cost functions, and NLP backends so teams run trajectory optimization and nonlinear MPC against ODE plants without assembling a solver stack from papers.
INTEGRATION GUIDE
1. Optimize robot trajectories with iLQR or Gauss-Newton multiple shooting
2. Run nonlinear MPC using IPOPT, SNOPT, or HPIPM backends
3. Model ODE plants and costs with autodiff-friendly C++ interfaces
4. Prototype motion planning and estimation loops before hardware tests
TAGS
cpproboticsmpcoptimal-controltrajectory-optimizationilqropen-source