Equality Constrained Linear Optimal Control With Factor Graphs

2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)(2021)

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摘要
This paper presents a novel factor graph-based approach to solve the discrete-time finite-horizon Linear Quadratic Regulator problem subject to auxiliary linear equality constraints within and across time steps. We represent such optimal control problems using constrained factor graphs and optimize the factor graphs to obtain the optimal trajectory and the feedback control policies using the variable elimination algorithm with a modified Gram-Schmidt process. We prove that our approach has the same order of computational complexity as the state-of-the-art dynamic programming approach. Furthermore, current dynamic programming approaches can only handle equality constraints between variables at the same time step, but ours can handle equality constraints among any combination of variables at any time step while maintaining linear complexity with respect to trajectory length. Our approach can be used to efficiently generate trajectories and feedback control policies to achieve periodic motion or repetitive manipulation.
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关键词
linear optimal control,factor graph-based approach,auxiliary linear equality constraints,time step,optimal control problems,constrained factor graphs,optimal trajectory,feedback control policies,variable elimination algorithm,modified Gram-Schmidt process,dynamic programming approach,current dynamic programming approaches,linear complexity,discrete-time finite-horizon linear quadratic regulator problem,equality constraints
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