96 citations · 267 across the 31 of their papers we have counts for
10 papers · 1 filter
Dynamic Inference on Graphs using Structured Transition Models
Saumya Saxena, Oliver Kroemer
Enabling robots to perform complex dynamic tasks such as picking up an object in one sweeping motion or pushing off a wall to quickly turn a corner is a challenging problem. The dy…
Focused Adaptation of Dynamics Models for Deformable Object Manipulation
Peter Mitrano, Alex LaGrassa, Oliver Kroemer +1
In order to efficiently learn a dynamics model for a task in a new environment, one can adapt a model learned in a similar source environment. However, existing adaptation methods…
Efficient Recovery Learning using Model Predictive Meta-Reasoning
Shivam Vats, Maxim Likhachev, Oliver Kroemer
Operating under real world conditions is challenging due to the possibility of a wide range of failures induced by execution errors and state uncertainty. In relatively benign sett…
Learning to Singulate Layers of Cloth using Tactile Feedback
Sashank Tirumala, Thomas Weng, Daniel Seita +3
Robotic manipulation of cloth has applications ranging from fabrics manufacturing to handling blankets and laundry. Cloth manipulation is challenging for robots largely due to thei…
DeltaZ: An Accessible Compliant Delta Robot Manipulator for Research and Education
Sarvesh Patil, Samuel C. Alvares, Pragna Mannam +2
This paper presents the DeltaZ robot, a centimeter-scale, low-cost, delta-style robot that allows for a broad range of capabilities and robust functionalities. Current technologies…
Learning Model Preconditions for Planning with Multiple Models
Alex LaGrassa, Oliver Kroemer
Different models can provide differing levels of fidelity when a robot is planning. Analytical models are often fast to evaluate but only work in limited ranges of conditions. Mean…
Learning Preconditions of Hybrid Force-Velocity Controllers for Contact-Rich Manipulation
Jacky Liang, Xianyi Cheng, Oliver Kroemer
Robots need to manipulate objects in constrained environments like shelves and cabinets when assisting humans in everyday settings like homes and offices. These constraints make ma…
Linear Delta Arrays for Compliant Dexterous Distributed Manipulation
Sarvesh Patil, Tony Tao, Tess Hellebrekers +2
This paper presents a new type of distributed dexterous manipulator: delta arrays. Our delta array setup consists of 64 linearly-actuated delta robots with 3D-printed compliant lin…
Synergistic Scheduling of Learning and Allocation of Tasks in Human-Robot Teams
Shivam Vats, Oliver Kroemer, Maxim Likhachev
We consider the problem of completing a set of tasks with a human-robot team using minimum effort. In many domains, teaching a robot to be fully autonomous can be counterproduc…
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
Sebastian Weichwald, Søren Wengel Mogensen, Tabitha Edith Lee +6
Questions in causality, control, and reinforcement learning go beyond the classical machine learning task of prediction under i.i.d. observations. Instead, these fields consider th…