A Factor-Graph Approach for Optimization Problems with Dynamics Constraints
This provides a flexible and insightful method for robotics optimization, though it appears incremental as it builds on existing factor graph and optimization techniques.
The paper tackles the problem of solving dynamics and kinodynamic motion planning problems by introducing dynamics factor graphs as a graphical framework, enabling the formulation of trajectory optimization with full consideration of whole-body dynamics and contacts, and demonstrates its application on systems from a cart pole to a 12-DoF quadrupedal robot.
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.