research
∙
07/11/2023
Forward Dynamics Estimation from Data-Driven Inverse Dynamics Learning
In this paper, we propose to estimate the forward dynamics equations of ...
share
research
∙
03/06/2023
Learning Object Manipulation With Under-Actuated Impulse Generator Arrays
For more than half a century, vibratory bowl feeders have been the stand...
research
∙
01/30/2023
Learning Control from Raw Position Measurements
We propose a Model-Based Reinforcement Learning (MBRL) algorithm named V...
research
∙
12/02/2022
Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control
Robots have been steadily increasing their presence in our daily lives, ...
research
∙
09/28/2022
Constrained Dynamic Movement Primitives for Safe Learning of Motor Skills
Dynamic movement primitives are widely used for learning skills which ca...
research
∙
04/22/2022
Design of Adaptive Compliance Controllers for Safe Robotic Assembly
Insertion operations are a critical element of most robotic assembly ope...
research
∙
11/20/2021
Imitation and Supervised Learning of Compliance for Robotic Assembly
We present the design of a learning-based compliance controller for asse...
research
∙
04/26/2021
Control of Mechanical Systems via Feedback Linearization Based on Black-Box Gaussian Process Models
In this paper, we consider the use of black-box Gaussian process (GP) mo...
research
∙
04/02/2021
Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry
Object insertion is a classic contact-rich manipulation task. The task r...
research
∙
01/28/2021
Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application
In this paper, we present a Model-Based Reinforcement Learning algorithm...
research
∙
01/21/2021
Model-based Policy Search for Partially Measurable Systems
In this paper, we propose a Model-Based Reinforcement Learning (MBRL) al...
research
∙
11/14/2020
Towards Human-Level Learning of Complex Physical Puzzles
Humans quickly solve tasks in novel systems with complex dynamics, witho...
research
∙
10/31/2020
Deep Reactive Planning in Dynamic Environments
The main novelty of the proposed approach is that it allows a robot to l...
research
∙
07/22/2020
Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks
One of the main challenges in peg-in-a-hole (PiH) insertion tasks is in ...
research
∙
03/03/2020
Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
Deep reinforcement learning (RL) algorithms have recently achieved remar...
research
∙
02/25/2020
Model-Based Reinforcement Learning for Physical Systems Without Velocity and Acceleration Measurements
In this paper, we propose a derivative-free model learning framework for...
research
∙
01/27/2020
Multi-label Prediction in Time Series Data using Deep Neural Networks
This paper addresses a multi-label predictive fault classification probl...
research
∙
01/22/2020
Local Policy Optimization for Trajectory-Centric Reinforcement Learning
The goal of this paper is to present a method for simultaneous trajector...
research
∙
10/23/2019
Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control
Robots need to learn skills that can not only generalize across similar ...
research
∙
03/13/2019
Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning
In this paper, we propose a reinforcement learning-based algorithm for t...
research
∙
12/22/2018
Learning Dynamical Demand Response Model in Real-Time Pricing Program
Price responsiveness is a major feature of end use customers (EUCs) that...
research
∙
09/13/2018
Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze
This paper presents a problem of model learning for the purpose of learn...
research
∙
09/13/2018
Learning Hybrid Models to Control a Ball in a Circular Maze
This paper presents a problem of model learning to navigate a ball to a ...
research
∙
09/13/2018
Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics
Learning robot tasks or controllers using deep reinforcement learning ha...
research
∙
06/13/2018
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
Recent work has shown that reinforcement learning (RL) is a promising ap...
research
∙
06/28/2017
