139 citations · 987 across the 58 of their papers we have counts for
11 papers · 1 filter
Learning from Guided Play: A Scheduled Hierarchical Approach for Improving Exploration in Adversarial Imitation Learning
Trevor Ablett, Bryan Chan, Jonathan Kelly
Effective exploration continues to be a significant challenge that prevents the deployment of reinforcement learning for many physical systems. This is particularly true for system…
Observability-Aware Trajectory Optimization: Theory, Viability, and State of the Art
Christopher Grebe, Emmett Wise, Jonathan Kelly
Ideally, robots should move in ways that maximize the knowledge gained about the state of both their internal system and the external operating environment. Trajectory design is a…
Convex Iteration for Distance-Geometric Inverse Kinematics
Matthew Giamou, Filip Marić, David M. Rosen +4
Inverse kinematics (IK) is the problem of finding robot joint configurations that satisfy constraints on the position or pose of one or more end-effectors. For robots with redundan…
Riemannian Optimization for Distance-Geometric Inverse Kinematics
Filip Marić, Matthew Giamou, Adam W. Hall +3
Solving the inverse kinematics problem is a fundamental challenge in motion planning, control, and calibration for articulated robots. Kinematic models for these robots are typical…
On the Coupling of Depth and Egomotion Networks for Self-Supervised Structure from Motion
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
Structure from motion (SfM) has recently been formulated as a self-supervised learning problem, where neural network models of depth and egomotion are learned jointly through view…
A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems
Jonathan Kelly, Christopher Grebe, Matthew Giamou
We examine the problem of time delay estimation, or temporal calibration, in the context of multisensor data fusion. Differences in processing intervals and other factors typically…