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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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Continuum Robot State Estimation with Actuation Uncertainty
A sparse factor-graph formulation of the discrete Cosserat rod with midpoint strain integration gives real-time joint estimation of shape, external loads, and actuation for tendon-driven, parallel, and concentric-tube...
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Barrier Method for Inequality Constrained Factor Graph Optimization with Application to Model Predictive Control
A barrier interior-point method is encoded as new inequality factor nodes in the g2o factor-graph solver, enabling MPC with inequality constraints in a unified optimization backend.
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