Author

Travis Manderson

2 papers indexed here

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Preprint Sep 2026

Planning along Differentiable Charts of Constraint Manifolds with General-Purpose IK Solvers

A new approach for computing gradients of analytic IK parameterizations is presented, using the inverse function theorem to recover the desired gradients from the ordinary forward kinematic Jacobian, and a least-squares domain extension and an optimization-amenable description of the reachability constraint are present...

Thomas Cohn, Seiji Shaw, Harel Biggie et al. · 2 citations

#artificial intelligence Jan 2026

Toward Learning POMDPs Beyond Full-Rank Actions and State Observability

It is shown how Predictive State Representations learn POMDP matrices up to a similarity transform, and this transform may be estimated via tensor decomposition methods, and it is shown that learning a POMDP beyond a partition of states is impossible from sequential data.

Seiji Shaw, Travis Manderson, Chad Kessens et al. · arXiv.org · 1 citation