68 citations · 196 across the 49 of their papers we have counts for
12 papers · 1 filter
On Hand-Held Grippers and the Morphological Gap in Human Manipulation Demonstration
Kiran Doshi, Yijiang Huang, Stelian Coros
Collecting manipulation demonstrations with robotic hardware is tedious - and thus difficult to scale. Recording data on robot hardware ensures that it is in the appropriate format…
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning
Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija +4
We introduce PACOH-RL, a novel model-based Meta-Reinforcement Learning (Meta-RL) algorithm designed to efficiently adapt control policies to changing dynamics. PACOH-RL meta-learns…
Ungar -- A C++ Framework for Real-Time Optimal Control Using Template Metaprogramming
Flavio De Vincenti, Stelian Coros
We present Ungar, an open-source library to aid the implementation of high-dimensional optimal control problems (OCPs). We adopt modern template metaprogramming techniques to enabl…
Embracing Safe Contacts with Contact-aware Planning and Control
Zhaoting Li, Miguel Zamora, Hehui Zheng +1
Unlike human beings that can employ the entire surface of their limbs as a means to establish contact with their environment, robots are typically programmed to interact with their…
No Free Slide: Spurious Contact Forces in Incremental Potential Contact
Yinwei Du, Yue Li, Stelian Coros +1
Modeling contact between deformable solids is a fundamental problem in computer animation, mechanical design, and robotics. Existing methods based on -discretizations -- piece…
TRTM: Template-based Reconstruction and Target-oriented Manipulation of Crumpled Cloths
Wenbo Wang, Gen Li, Miguel Zamora +1
Precise reconstruction and manipulation of the crumpled cloths is challenging due to the high dimensionality of cloth models, as well as the limited observation at self-occluded re…
Optimistic Active Exploration of Dynamical Systems
Bhavya Sukhija, Lenart Treven, Cansu Sancaktar +3
Reinforcement learning algorithms commonly seek to optimize policies for solving one particular task. How should we explore an unknown dynamical system such that the estimated mode…
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization
Daniel Widmer, Dongho Kang, Bhavya Sukhija +3
This paper presents a data-driven strategy to streamline the deployment of model-based controllers in legged robotic hardware platforms. Our approach leverages a model-free safe le…
Differentiable Stripe Patterns for Inverse Design of Structured Surfaces
Juan Montes Maestre, Yinwei Du, Ronan Hinchet +2
Stripe patterns are ubiquitous in nature and everyday life. While the synthesis of these patterns has been thoroughly studied in the literature, their potential to control the mech…
RL + Model-based Control: Using On-demand Optimal Control to Learn Versatile Legged Locomotion
Dongho Kang, Jin Cheng, Miguel Zamora +2
This paper presents a control framework that combines model-based optimal control and reinforcement learning (RL) to achieve versatile and robust legged locomotion. Our approach en…
Differentiable Task Assignment and Motion Planning
Jimmy Envall, Roi Poranne, Stelian Coros
Task and motion planning is one of the key problems in robotics today. It is often formulated as a discrete task allocation problem combined with continuous motion planning. Many e…
Efficient Learning of High Level Plans from Play
Núria Armengol Urpí, Marco Bagatella, Otmar Hilliges +2
Real-world robotic manipulation tasks remain an elusive challenge, since they involve both fine-grained environment interaction, as well as the ability to plan for long-horizon goa…