Author name cluster

Xingyu Yang

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5 papers

2 author rows

AAAI Conference 2024 Conference Paper

Decomposing Semantic Shifts for Composed Image Retrieval

Xingyu Yang
Daqing Liu
Heng Zhang
Yong Luo
Chaoyue Wang
Jing Zhang

Composed image retrieval is a type of image retrieval task where the user provides a reference image as a starting point and specifies a text on how to shift from the starting point to the desired target image. However, most existing methods focus on the composition learning of text and reference images and oversimplify the text as a description, neglecting the inherent structure and the user's shifting intention of the texts. As a result, these methods typically take shortcuts that disregard the visual cue of the reference images. To address this issue, we reconsider the text as instructions and propose a Semantic Shift Network (SSN) that explicitly decomposes the semantic shifts into two steps: from the reference image to the visual prototype and from the visual prototype to the target image. Specifically, SSN explicitly decomposes the instructions into two components: degradation and upgradation, where the degradation is used to picture the visual prototype from the reference image, while the upgradation is used to enrich the visual prototype into the final representations to retrieve the desired target image. The experimental results show that the proposed SSN demonstrates a significant improvement of 5.42% and 1.37% on the CIRR and FashionIQ datasets, respectively, and establishes a new state-of-the-art performance. The code is available at https://github.com/starxing-yuu/SSN.

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NeurIPS Conference 2024 Conference Paper

The Road Less Scheduled

Aaron Defazio
Xingyu Yang
Harsh Mehta
Konstantin Mishchenko
Ahmed Khaled
Ashok Cutkosky

Existing learning rate schedules that do not require specification of the optimization stopping step $T$ are greatly out-performed by learning rate schedules that depend on $T$. We propose an approach that avoids the need for this stopping time by eschewing the use of schedules entirely, while exhibiting state-of-the-art performance compared to schedules across a wide family of problems ranging from convex problems to large-scale deep learning problems. Our Schedule-Free approach introduces no additional hyper-parameters over standard optimizers with momentum. Our method is a direct consequence of a new theory we develop that unifies scheduling and iterate averaging. An open source implementation of our method is available at https: //github. com/facebookresearch/schedule_free. Schedule-Free AdamW is the core algorithm behind our winning entry to the MLCommons 2024 AlgoPerf Algorithmic Efficiency Challenge Self-Tuning track.

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ICRA Conference 2022 Conference Paper

A Switchable Rigid-Continuum Robot Arm: Design and Testing

Hao Wang
Zhengxue Zhou
Xingyu Yang
Xuping Zhang

This paper presents a novel robot arm that is capable of switching between a rigid robot arm and a continuum robot arm. Therefore, the novel robot arm can perform adaptive physical interaction and manipulation against complex working environments and tasks. The switch-ability of the robot arm is achieved with two types of joints: knee-like flexible joints and continuum flexible joints, with which the continuum segment of the robot arm is capable of locking and losing, hence the degree of freedom of the robot arm is capable to be switched. In this work, kinematics is established for specifying the relationship between joints space and global coordinates in both rigid and continuum configurations. Then, the posture and workspace in rigid and continuum configurations are analyzed and illustrated with numerical simulations, and compared based on the established kinematic model. Finally, a series of preliminary experimental testing toward the joint motion and stiffness has been carried out to validate the design, the kinematic model, and the motion performance of the proposed robot arm. Both the numerical and experimental results show that the knee-like joints can guarantee favorable motion accuracy, and the motion of continuum segment from the testing is well aligned with the motion calculated from the theoretical model. Moreover, the stiffness of rigid configuration is larger than the continuum configuration based on the stiffness experiment results. Therefore, the proposed novel robot arm is capable to handle adaptive interaction and manipulation in a diverse environment through the switching between the rigid and continuum configurations.

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ICRA Conference 2022 Conference Paper

Digital Twin with Integrated Robot-Human/Environment Interaction Dynamics for an Industrial Mobile Manipulator

Zhengxue Zhou
Xingyu Yang
Hao Wang
Xuping Zhang

To achieve real-time dynamic simulation analysis and optimization design, a dynamic digital twin of a nonholonomic mobile manipulator (one UR5e mounted on an industrial mobile robot MIR 200) has been developed in this paper. First, the digital twin integrated with dynamics of a mobile manipulator is established. The framework of the dynamic digital twin is presented in detail. Then, the dynamic model of the system has been established with the consideration of the physical interaction between the robot and humans/environments using Lagrange formulation. Finally, the experimental testing has been conducted to validate the dynamic model and evaluate the performances (such as real-time property, accuracy, etc.) of the dynamic digital twin that is integrated with the physical human/environment-robot interaction.

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ICRA Conference 2022 Conference Paper

Dynamic Modeling and Digital Twin of a Harmonic Drive Based Collaborative Robot Joint

Xingyu Yang
Dong Qiang
Zixuan Chen
Hao Wang
Zhengxue Zhou
Xuping Zhang

Collaborative robots are gradually taking over the leading position in automating the production and manufacturing of the SMEs, where the human-robot collaboration is highly emphasized. Therefore, estimating the force and simulating the performance of robots are of great importance. As a newly introduced technology, digital twin, has gained more attentions for simulation, process evaluation, real-time monitoring, etc. However, the current state-of-the-art of digital twin for robots still remains on the kinematic level, and the integrated robot system dynamics is too complex to be incorporated into the digital twin. Therefore, this research starts with the perspective of harmonic drive based robot joint, and proposes a dynamic model of robot joint by analyzing the composition, transmission principle, and internal interactions. Then the experimental parameter identification is performed to obtain the inherent parameters, which can reflect the system performance characteristics. Finally, a preliminary digital twin of robot joint integrated with dynamic model is established with Gazebo and MATLAB. The proposed approach could be used to simulate the dynamic behavior of robot joint in real time and make contributions to the state of the art for digital twin.

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