A Factor-Graph Approach for Optimization Problems with Dynamics Constraints
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In this paper, we introduce dynamics factor graphs as a graphical framework to solve dynamics problems and kinodynamic motion planning problems with full consideration of whole-body dynamics and contacts. A factor graph representation of dynamics problems provides an insightful visualization of their mathematical structure and can be used in conjunction with sparse nonlinear optimizers to solve challenging, high-dimensional optimization problems in robotics. We can easily formulate kinodynamic motion planning as a trajectory optimization problem with factor graphs. We demonstrate the flexibility and descriptive power of dynamics factor graphs by applying them to control various dynamical systems, ranging from a simple cart pole to a 12-DoF quadrupedal robot.
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Cited by 2 Pith papers
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DynoJEPP: Joint Estimation, Prediction and Planning in Dynamic Environments
DynoJEPP introduces directed factors in factor graphs to jointly optimize estimation, prediction, and planning while preventing feedback corruption that causes unsafe behavior in dynamic environments.
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