96 citations · 267 across the 31 of their papers we have counts for
36 papers
Enhancing Dexterity in Robotic Manipulation via Hierarchical Contact Exploration
Xianyi Cheng, Sarvesh Patil, Zeynep Temel +2
Planning robot dexterity is challenging due to the non-smoothness introduced by contacts, intricate fine motions, and ever-changing scenarios. We present a hierarchical planning fr…
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…
Search-Based Task Planning with Learned Skill Effect Models for Lifelong Robotic Manipulation
Jacky Liang, Mohit Sharma, Alex LaGrassa +3
Robots deployed in many real-world settings need to be able to acquire new skills and solve new tasks over time. Prior works on planning with skills often make assumptions on the s…
Mission-level Robustness with Rapidly-deployed, Autonomous Aerial Vehicles by Carnegie Mellon Team Tartan at MBZIRC 2020
Anish Bhattacharya, Akshit Gandhi, Lukas Merkle +7
For robotic systems to succeed in high risk, real-world situations, they have to be quickly deployable and robust to environmental changes, under-performing hardware, and mission s…
Adaptive Sampling: Algorithmic vs. Human Waypoint Selection
Stephanie Kemna, Sara Kangaslahti, Oliver Kroemer +1
Robots are used for collecting samples from natural environments to create models of, for example, temperature or algae fields in the ocean. Adaptive informative sampling is a prov…
Learning Reactive and Predictive Differentiable Controllers for Switching Linear Dynamical Models
Saumya Saxena, Alex LaGrassa, Oliver Kroemer
Humans leverage the dynamics of the environment and their own bodies to accomplish challenging tasks such as grasping an object while walking past it or pushing off a wall to turn…
Generalizing Object-Centric Task-Axes Controllers using Keypoints
Mohit Sharma, Oliver Kroemer
To perform manipulation tasks in the real world, robots need to operate on objects with various shapes, sizes and without access to geometric models. It is often unfeasible to trai…
Causal Reasoning in Simulation for Structure and Transfer Learning of Robot Manipulation Policies
Tabitha Edith Lee, Jialiang Zhao, Amrita S. Sawhney +2
We present CREST, an approach for causal reasoning in simulation to learn the relevant state space for a robot manipulation policy. Our approach conducts interventions using intern…
Playing with Food: Learning Food Item Representations through Interactive Exploration
Amrita Sawhney, Steven Lee, Kevin Zhang +2
A key challenge in robotic food manipulation is modeling the material properties of diverse and deformable food items. We propose using a multimodal sensory approach to interact an…
Relational Learning for Skill Preconditions
Mohit Sharma, Oliver Kroemer
To determine if a skill can be executed in any given environment, a robot needs to learn the preconditions for the skill. As robots begin to operate in dynamic and unstructured env…
Visual Identification of Articulated Object Parts
Vicky Zeng, Tabitha Edith Lee, Jacky Liang +1
As autonomous robots interact and navigate around real-world environments such as homes, it is useful to reliably identify and manipulate articulated objects, such as doors and cab…
Learning to Compose Hierarchical Object-Centric Controllers for Robotic Manipulation
Mohit Sharma, Jacky Liang, Jialiang Zhao +2
Manipulation tasks can often be decomposed into multiple subtasks performed in parallel, e.g., sliding an object to a goal pose while maintaining contact with a table. Individual s…
Towards Robotic Assembly by Predicting Robust, Precise and Task-oriented Grasps
Jialiang Zhao, Daniel Troniak, Oliver Kroemer
Robust task-oriented grasp planning is vital for autonomous robotic precision assembly tasks. Knowledge of the objects' geometry and preconditions of the target task should be inco…
A Modular Robotic Arm Control Stack for Research: Franka-Interface and FrankaPy
Kevin Zhang, Mohit Sharma, Jacky Liang +1
We designed a modular robotic control stack that provides a customizable and accessible interface to the Franka Emika Panda Research robot. This framework abstracts high-level robo…
Contact Localization for Robot Arms in Motion without Torque Sensing
Jacky Liang, Oliver Kroemer
Detecting and localizing contacts is essential for robot manipulators to perform contact-rich tasks in unstructured environments. While robot skins can localize contacts on the sur…