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05/17/2023
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies
Robots often rely on a repertoire of previously-learned motion policies ...
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04/20/2023
The e-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing
Robotic manipulation is currently undergoing a profound paradigm shift d...
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11/06/2022
Learning Riemannian Stable Dynamical Systems via Diffeomorphisms
Dexterous and autonomous robots should be capable of executing elaborate...
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10/04/2022
Bringing robotics taxonomies to continuous domains via GPLVM on hyperbolic manifolds
Robotic taxonomies have appeared as high-level hierarchical abstractions...
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09/07/2022
Optimizing Demonstrated Robot Manipulation Skills for Temporal Logic Constraints
For performing robotic manipulation tasks, the core problem is determini...
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03/15/2022
Reactive Motion Generation on Learned Riemannian Manifolds
In recent decades, advancements in motion learning have enabled robots t...
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11/02/2021
Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels
Bayesian optimization is a data-efficient technique which can be used fo...
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10/28/2021
Orientation Probabilistic Movement Primitives on Riemannian Manifolds
Learning complex robot motions necessarily demands to have models that a...
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10/01/2021
Study of Signal Temporal Logic Robustness Metrics for Robotic Tasks Optimization
Signal Temporal Logic (STL) is an efficient technique for describing tem...
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09/09/2021
Learning Forceful Manipulation Skills from Multi-modal Human Demonstrations
Learning from Demonstration (LfD) provides an intuitive and fast approac...
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06/08/2021
Learning Riemannian Manifolds for Geodesic Motion Skills
For robots to work alongside humans and perform in unstructured environm...
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10/21/2020
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds
Despite the recent success of Bayesian optimization (BO) in a variety of...
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08/24/2020
Learning and Sequencing of Object-Centric Manipulation Skills for Industrial Tasks
Enabling robots to quickly learn manipulation skills is an important, ye...
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08/04/2020
Analysis and Transfer of Human Movement Manipulability in Industry-like Activities
Humans exhibit outstanding learning, planning and adaptation capabilitie...
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10/11/2019
Bayesian Optimization Meets Riemannian Manifolds in Robot Learning
Bayesian optimization (BO) recently became popular in robotics to optimi...
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08/20/2019
Interactive Trajectory Adaptation through Force-guided Bayesian Optimization
Flexible manufacturing processes demand robots to easily adapt to change...
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05/23/2019
Hierarchical Reinforcement Learning for Concurrent Discovery of Compound and Composable Policies
A common strategy to deal with the expensive reinforcement learning (RL)...
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03/05/2019
Uncertainty-Aware Imitation Learning using Kernelized Movement Primitives
During the past few years, probabilistic approaches to imitation learnin...
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11/27/2018
Geometry-aware Manipulability Transfer
Body posture influences human and robots performance in manipulation tas...
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12/19/2017