84 citations · 200 across the 19 of their papers we have counts for
9 papers · 1 filter
CMAX++ : Leveraging Experience in Planning and Execution using Inaccurate Models
Anirudh Vemula, J. Andrew Bagnell, Maxim Likhachev
Given access to accurate dynamical models, modern planning approaches are effective in computing feasible and optimal plans for repetitive robotic tasks. However, it is difficult t…
TRON: A Fast Solver for Trajectory Optimization with Non-Smooth Cost Functions
Anirudh Vemula, J. Andrew Bagnell
Trajectory optimization is an important tool for control and planning of complex, underactuated robots, and has shown impressive results in real world robotic tasks. However, in ap…
Planning and Execution using Inaccurate Models with Provable Guarantees
Anirudh Vemula, Yash Oza, J. Andrew Bagnell +1
Models used in modern planning problems to simulate outcomes of real world action executions are becoming increasingly complex, ranging from simulators that do physics-based reason…
An Algorithmic Perspective on Imitation Learning
Takayuki Osa, Joni Pajarinen, Gerhard Neumann +3
As robots and other intelligent agents move from simple environments and problems to more complex, unstructured settings, manually programming their behavior has become increasingl…
Shared Autonomy via Hindsight Optimization for Teleoperation and Teaming
Shervin Javdani, Henny Admoni, Stefania Pellegrinelli +2
In shared autonomy, a user and autonomous system work together to achieve shared goals. To collaborate effectively, the autonomous system must know the user's goal. As such, most p…
A Fast Stochastic Contact Model for Planar Pushing and Grasping: Theory and Experimental Validation
Jiaji Zhou, J. Andrew Bagnell, Matthew T. Mason
Based on the convex force-motion polynomial model for quasi-static sliding, we derive the kinematic contact model to determine the contact modes and instantaneous object motion on…