14 citations · 21 across the 5 of their papers we have counts for
8 papers · 1 filter
On the Utility of Koopman Operator Theory in Learning Dexterous Manipulation Skills
Yunhai Han, Mandy Xie, Ye Zhao +1
Despite impressive dexterous manipulation capabilities enabled by learning-based approaches, we are yet to witness widespread adoption beyond well-resourced laboratories. This is l…
Imitation Learning via Simultaneous Optimization of Policies and Auxiliary Trajectories
Mandy Xie, Anqi Li, Karl Van Wyk +3
Imitation learning (IL) is a frequently used approach for data-efficient policy learning. Many IL methods, such as Dataset Aggregation (DAgger), combat challenges like distribution…
RMP2: A Structured Composable Policy Class for Robot Learning
Anqi Li, Ching-An Cheng, M. Asif Rana +4
We consider the problem of learning motion policies for acceleration-based robotics systems with a structured policy class specified by RMPflow. RMPflow is a multi-task control fra…
A Factor-Graph Approach for Optimization Problems with Dynamics Constraints
Mandy Xie, Alejandro Escontrela, Frank Dellaert
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-bod…
Generalized Nonlinear and Finsler Geometry for Robotics
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie +2
Robotics research has found numerous important applications of Riemannian geometry. Despite that, the concept remain challenging to many roboticists because the background material…
Optimization Fabrics
Nathan D. Ratliff, Karl Van Wyk, Mandy Xie +2
This paper presents a theory of optimization fabrics, second-order differential equations that encode nominal behaviors on a space and can be used to define the behavior of a smoot…