1 citations · 1 across the 3 of their papers we have counts for
5 papers
Latent Space Planning for Multi-Object Manipulation with Environment-Aware Relational Classifiers
Yixuan Huang, Nichols Crawford Taylor, Adam Conkey +2
Objects rarely sit in isolation in everyday human environments. If we want robots to operate and perform tasks in our human environments, they must understand how the objects they…
Planning for Multi-Object Manipulation with Graph Neural Network Relational Classifiers
Yixuan Huang, Adam Conkey, Tucker Hermans
Objects rarely sit in isolation in human environments. As such, we'd like our robots to reason about how multiple objects relate to one another and how those relations may change a…
Planning under Uncertainty to Goal Distributions
Adam Conkey, Tucker Hermans
Goals for planning problems are typically conceived of as subsets of the state space. However, for many practical planning problems in robotics, we expect the robot to predict goal…
Active Learning of Probabilistic Movement Primitives
Adam Conkey, Tucker Hermans
A Probabilistic Movement Primitive (ProMP) defines a distribution over trajectories with an associated feedback policy. ProMPs are typically initialized from human demonstrations a…
Learning Task Constraints from Demonstration for Hybrid Force/Position Control
Adam Conkey, Tucker Hermans
We present a novel method for learning hybrid force/position control from demonstration. We learn a dynamic constraint frame aligned to the direction of desired force using Cartesi…