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Title: GitHub - arcuma/ocpy: Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation.

Open Graph Title: GitHub - arcuma/ocpy: Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation.

X Title: GitHub - arcuma/ocpy: Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation.

Description: Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation. - arcuma/ocpy

Open Graph Description: Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation. - arcuma/ocpy

X Description: Optimal control solver implemented in Python. SymPy for symbolic differentiation and Numba for fast computation. - arcuma/ocpy

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https://patch-diff.githubusercontent.com/arcuma/ocpy#references
D. H. Jacobson and D. Q. Mayne, Differential Dynamic Programming, Elsevier, 1970.https://doi.org/10.1016/B978-0-12-012710-8.50010-8
Y. Tassa, T. Erez and E. Todorov, Synthesis and stabilization of complex behaviors through online trajectory optimization, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4906-4913, 2012.https://doi.org/10.1109/IROS.2012.6386025
S. Katayama, Fast Model Predictive Control of Robotic Systems with Rigid Contacts. Kyoto University, 2022.https://doi.org/10.14989/doctor.k24266
J. Nocedal and S.J. Wright, Numerical Optimization (2nd ed.). Springer, 2006.https://doi.org/10.1007/978-0-387-40065-5
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