A modular robotic arm control stack for research: Franka-interface and frankapy
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 …
interface to the Franka Emika Panda Research robot. This framework abstracts high-level …
Crossing the gap: A deep dive into zero-shot sim-to-real transfer for dynamics
Zero-shot sim-to-real transfer of tasks with complex dynamics is a highly challenging and
unsolved problem. A number of solutions have been proposed in recent years, but we have …
unsolved problem. A number of solutions have been proposed in recent years, but we have …
Droid: Minimizing the reality gap using single-shot human demonstration
Reinforcement learning (RL) has demonstrated great success in the past several years.
However, most of the scenarios focus on simulated environments. One of the main …
However, most of the scenarios focus on simulated environments. One of the main …
Adaptive robotic information gathering via non-stationary Gaussian processes
Robotic Information Gathering (RIG) is a foundational research topic that answers how a
robot (team) collects informative data to efficiently build an accurate model of an unknown …
robot (team) collects informative data to efficiently build an accurate model of an unknown …
Registration of deformed tissue: A gnn-vae approach with data assimilation for sim-to-real transfer
M Afshar, T Meyer, RS Sloboda… - IEEE/ASME …, 2023 - ieeexplore.ieee.org
In image-guided surgery, deformation of soft tissues can cause substantial errors in targeting
internal targets, since deformation can affect the translation of preoperative image-based …
internal targets, since deformation can affect the translation of preoperative image-based …
Adaptsim: Task-driven simulation adaptation for sim-to-real transfer
Simulation parameter settings such as contact models and object geometry approximations
are critical to training robust robotic policies capable of transferring from simulation to real …
are critical to training robust robotic policies capable of transferring from simulation to real …
Learning to ground objects for robot task and motion planning
Task and motion planning (TAMP) algorithms have been developed to help robots plan
behaviors in discrete and continuous spaces. Robots face complex real-world scenarios …
behaviors in discrete and continuous spaces. Robots face complex real-world scenarios …
CyberDemo: Augmenting Simulated Human Demonstration for Real-World Dexterous Manipulation
We introduce CyberDemo, a novel approach to robotic imitation learning that leverages
simulated human demonstrations for real-world tasks. By incorporating extensive data …
simulated human demonstrations for real-world tasks. By incorporating extensive data …
Mnemosyne: Learning to Train Transformers with Transformers
In this work, we propose a new class of learnable optimizers, called Mnemosyne. It is based
on the novel spatio-temporal low-rank implicit attention Transformers that can learn to train …
on the novel spatio-temporal low-rank implicit attention Transformers that can learn to train …