Yongjia Zhao
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View article: LLMs augmented hierarchical reinforcement learning with action primitives for long-horizon manipulation tasks
LLMs augmented hierarchical reinforcement learning with action primitives for long-horizon manipulation tasks Open
View article: Efficient prediction of aerodynamic forces in rarefied flow using convolutional neural network based multi-process method
Efficient prediction of aerodynamic forces in rarefied flow using convolutional neural network based multi-process method Open
The direct simulation Monte Carlo (DSMC) is a widely used approach for studying aerodynamics effects of rarefied flows, but it is highly time-consuming and may exhibit statistical fluctuations. In this study, we propose an efficient aerody…
View article: Tube-MPC based trajectory tracking control for substation inspection robot
Tube-MPC based trajectory tracking control for substation inspection robot Open
A Tube-MPC based trajectory tracking control method was developed to enhance the capabilities of substation inspection robots. First, the kinematic models of the inspection robots were established, and the general form of the optimization …
View article: Real-Time Learning and Recognition of Assembly Activities Based on Virtual Reality Demonstration
Real-Time Learning and Recognition of Assembly Activities Based on Virtual Reality Demonstration Open
Teaching robots to learn through human demonstrations is a natural and direct method, and virtual reality technology is an effective way to achieve fast and realistic demonstrations. In this paper, we construct a virtual reality demonstrat…
View article: Learning to Have a Civil Aircraft Take Off under Crosswind Conditions by Reinforcement Learning with Multimodal Data and Preprocessing Data
Learning to Have a Civil Aircraft Take Off under Crosswind Conditions by Reinforcement Learning with Multimodal Data and Preprocessing Data Open
Autopilot technology in the field of aviation has developed over many years. However, it is difficult for an autopilot system to autonomously operate a civil aircraft under bad weather conditions. In this paper, we present a reinforcement …
View article: Policy Return: A New Method for Reducing the Number of Experimental Trials in Deep Reinforcement Learning
Policy Return: A New Method for Reducing the Number of Experimental Trials in Deep Reinforcement Learning Open
Using the same algorithm and hyperparameter configurations, deep reinforcement learning (DRL) will derive drastically different results from multiple experimental trials, and most of these results are unsatisfactory. Because of the instabi…
View article: Fast and Robust Monocular Visua-Inertial Odometry Using Points and Lines
Fast and Robust Monocular Visua-Inertial Odometry Using Points and Lines Open
When the camera moves quickly and the image is blurred or the texture in the scene is missing, the Simultaneous Localization and Mapping (SLAM) algorithm based on point feature experiences difficulty tracking enough effective feature point…
View article: 3D recognition based on ordered images reconstruction
3D recognition based on ordered images reconstruction Open
Nowadays, more and more applications require precise and quickly 3D recognition, such as augmented reality and robot navigation. In recent years, model-based methods can get accurate object or scene recognition, but it takes a lot of time …
View article: Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network
Wearable Device-Based Gait Recognition Using Angle Embedded Gait Dynamic Images and a Convolutional Neural Network Open
The widespread installation of inertial sensors in smartphones and other wearable devices provides a valuable opportunity to identify people by analyzing their gait patterns, for either cooperative or non-cooperative circumstances. However…