REVIEW 2 cited by
A Factor-Graph Approach for Optimization Problems with Dynamics Constraints
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
A Factor-Graph Approach for Optimization Problems with Dynamics Constraints
read the original abstract
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.
Forward citations
Cited by 2 Pith papers
-
CMC-Opt: Constraint Manifold with Corners for Inequality-Constrained Optimization
Proposes constraint manifolds with corners as a new topological structure for mixed-constraint optimization in robotics, enabling direct unconstrained optimization on the feasible set.
-
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.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.