297 citations · 336 across the 18 of their papers we have counts for
20 papers
Perceptive Humanoid Motion from Simulation
Siyuan Hu, Abulikemu Abuduweili, Yue Meng +5
Humanoid robots have the potential to automate a wide range of physical tasks. Progress toward generalist humanoid autonomy, however, remains constrained by a data bottleneck: mapp…
Scaling Law of Neural Koopman Operators
Abulikemu Abuduweili, Yuyang Pang, Feihan Li +1
Data-driven neural Koopman operator theory has emerged as a powerful tool for linearizing and controlling nonlinear robotic systems. However, the performance of these data-driven m…
Trends in Motion Prediction Toward Deployable and Generalizable Autonomy: A Revisit and Perspectives
Letian Wang, Marc-Antoine Lavoie, Sandro Papais +13
Motion prediction, recently popularized as world models, refers to the anticipation of future agent states or scene evolution, which is rooted in human cognition, bridging percepti…
Enhancing Sample Generation of Diffusion Models using Noise Level Correction
Abulikemu Abuduweili, Chenyang Yuan, Changliu Liu +1
The denoising process of diffusion models can be interpreted as an approximate projection of noisy samples onto the data manifold. Moreover, the noise level in these samples approx…
Revisiting the Initial Steps in Adaptive Gradient Descent Optimization
Abulikemu Abuduweili, Changliu Liu
Adaptive gradient optimization methods, such as Adam, are prevalent in training deep neural networks across diverse machine learning tasks due to their ability to achieve faster co…
Robustifying Long-term Human-Robot Collaboration through a Multimodal and Hierarchical Framework
Peiqi Yu, Abulikemu Abuduweili, Ruixuan Liu +1
Long-term Human-Robot Collaboration (HRC) is crucial for enabling flexible manufacturing systems and integrating companion robots into daily human environments over extended period…
Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots
Feihan Li, Abulikemu Abuduweili, Yifan Sun +3
The control of legged robots, particularly humanoid and quadruped robots, presents significant challenges due to their high-dimensional and nonlinear dynamics. While linear systems…
Estimating Neural Network Robustness via Lipschitz Constant and Architecture Sensitivity
Abulikemu Abuduweili, Changliu Liu
Ensuring neural network robustness is essential for the safe and reliable operation of robotic learning systems, especially in perception and decision-making tasks within real-worl…
WeHelp: A Shared Autonomy System for Wheelchair Users
Abulikemu Abuduweili, Alice Wu, Tianhao Wei +1
There is a large population of wheelchair users. Most of the wheelchair users need help with daily tasks. However, according to recent reports, their needs are not properly satisfi…
KOROL: Learning Visualizable Object Feature with Koopman Operator Rollout for Manipulation
Hongyi Chen, Abulikemu Abuduweili, Aviral Agrawal +4
Learning dexterous manipulation skills presents significant challenges due to complex nonlinear dynamics that underlie the interactions between objects and multi-fingered hands. Ko…
Proactive Human-Robot Co-Assembly: Leveraging Human Intention Prediction and Robust Safe Control
Ruixuan Liu, Rui Chen, Abulikemu Abuduweili +1
Human-robot collaboration (HRC) is one key component to achieving flexible manufacturing to meet the different needs of customers. However, it is difficult to build intelligent rob…
General Place Recognition Survey: Towards the Real-world Autonomy Age
Peng Yin, Shiqi Zhao, Ivan Cisneros +6
Place recognition is the fundamental module that can assist Simultaneous Localization and Mapping (SLAM) in loop-closure detection and re-localization for long-term navigation. The…
BioSLAM: A Bio-inspired Lifelong Memory System for General Place Recognition
Peng Yin, Abulikemu Abuduweili, Shiqi Zhao +2
We present BioSLAM, a lifelong SLAM framework for learning various new appearances incrementally and maintaining accurate place recognition for previously visited areas. Unlike hum…
An Optical Control Environment for Benchmarking Reinforcement Learning Algorithms
Abulikemu Abuduweili, Changliu Liu
Deep reinforcement learning has the potential to address various scientific problems. In this paper, we implement an optics simulation environment for reinforcement learning based…
Escaping the Big Data Paradigm with Compact Transformers
Ali Hassani, Steven Walton, Nikhil Shah +3
With the rise of Transformers as the standard for language processing, and their advancements in computer vision, there has been a corresponding growth in parameter size and amount…
Adaptive Consistency Regularization for Semi-Supervised Transfer Learning
Abulikemu Abuduweili, Xingjian Li, Humphrey Shi +2
While recent studies on semi-supervised learning have shown remarkable progress in leveraging both labeled and unlabeled data, most of them presume a basic setting of the model is…
Robust Online Model Adaptation by Extended Kalman Filter with Exponential Moving Average and Dynamic Multi-Epoch Strategy
Abulikemu Abuduweili, Changliu Liu
High fidelity behavior prediction of intelligent agents is critical in many applications. However, the prediction model trained on the training set may not generalize to the testin…
Adaptable Human Intention and Trajectory Prediction for Human-Robot Collaboration
Abulikemu Abuduweili, Siyan Li, Changliu Liu
To engender safe and efficient human-robot collaboration, it is critical to generate high-fidelity predictions of human behavior. The challenges in making accurate predictions lie…
Efficient Method for Categorize Animals in the Wild
Abulikemu Abuduweili, Xin Wu, Xingchen Tao
Automatic species classification in camera traps would greatly help the biodiversity monitoring and species analysis in the earth. In order to accelerate the development of automat…
Automatic Generation of Personalized Comment Based on User Profile
Wenhuan Zeng, Abulikemu Abuduweili, Lei Li +1
Comments on social media are very diverse, in terms of content, style and vocabulary, which make generating comments much more challenging than other existing natural language gene…