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08/22/2022
Unscented Kalman filter with stable embedding for simple, accurate and computationally efficient state estimation of systems on manifolds in Euclidean space
This paper proposes a simple, accurate and computationally efficient met...
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05/12/2022
Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs
The optimization with orthogonality has been shown useful in training de...
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05/27/2021
Robust Navigation for Racing Drones based on Imitation Learning and Modularization
This paper presents a vision-based modularized drone racing navigation s...
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12/29/2020
The Adaptive Dynamic Programming Toolbox
The paper develops the Adaptive Dynamic Programming Toolbox (ADPT), whic...
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07/16/2019
Deep Reinforcement Learning Based Robot Arm Manipulation with Efficient Training Data through Simulation
Deep reinforcement learning trains neural networks using experiences sam...
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07/16/2019
Improved Reinforcement Learning through Imitation Learning Pretraining Towards Image-based Autonomous Driving
We present a training pipeline for the autonomous driving task given the...
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07/15/2019
A Dual Memory Structure for Efficient Use of Replay Memory in Deep Reinforcement Learning
In this paper, we propose a dual memory structure for reinforcement lear...
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06/17/2019
Robotic Navigation using Entropy-Based Exploration
Robotic navigation concerns the task in which a robot should be able to ...
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06/17/2019
Learning-Driven Exploration for Reinforcement Learning
Deep reinforcement learning algorithms have been shown to learn complex ...
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05/21/2019
Stochastic Inverse Reinforcement Learning
Inverse reinforcement learning (IRL) is an ill-posed inverse problem sin...
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02/28/2019
Interaction-aware Kalman Neural Networks for Trajectory Prediction
Forecasting the motion of surrounding dynamic obstacles (vehicles, bicyc...
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11/22/2018
Towards Robust Neural Networks with Lipschitz Continuity
Deep neural networks have shown remarkable performance across a wide ran...
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07/10/2018
On Controller Design for Systems on Manifolds in Euclidean Space
A new method is developed to design controllers in Euclidean space for s...
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10/05/2016
A Novel Representation of Neural Networks
Deep Neural Networks (DNNs) have become very popular for prediction in m...
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08/15/2016