Author name cluster

Hanlin Wang

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7 papers

2 author rows

YNIMG Journal 2026 Journal Article

The individual alpha bandwidth: A trait-like neural marker associated with sensory processing and executive function

Zeliang Jiang
Pan Zhang
Hanlin Wang
Wenxiao Zhong
Xingwei An
Zhijie Zhang

Alpha oscillations are a fundamental rhythm of human brain activity, yet most studies have emphasized the peak alpha frequency (IAF) while overlooking the width of the alpha band. Here, we examined the individual alpha bandwidth (IAB) as a complementary marker across four EEG datasets. Using a unified preprocessing pipeline, we assessed its reliability and functional relevance. Test-retest analyses showed good-to-excellent reliability, supporting its trait-like stability. Importantly, IAB estimated with the Savitzky-Golay filter (SGF) method-but not with FOOOF or amplitude-difference-was significantly related to sensory and cognitive processes, whereas IAF showed no such associations. In perception, wider parieto-occipital IAB during eyes-closed rest was associated with larger P2 amplitudes in visual and auditory evoked potentials. In cognition, wider parieto-occipital IAB during eyes-open rest was linked to smaller flanker interference effects and enhanced N450 amplitudes. Mediation analysis further revealed a significant indirect effect of N450 on the IAB-inhibitory control relationship, whereas the direct effect was not significant. These findings suggest that IAB reflects both perceptual and executive processes, but its functional relevance is constrained by methodological and experimental factors. Specifically, associations were method-dependent (emerging only with SGF), state-dependent (perception during eyes-closed rest, cognition during eyes-open rest), and in the cognitive domain, also frequency-window dependent (significant only within 6-14 Hz). Overall, this study establishes IAB as a reliable neural marker of individual differences in sensory and executive function while underscoring key methodological considerations for future research.

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IROS Conference 2025 Conference Paper

An insect-scale multimodal amphibious piezoelectric robot

Le Wang
Xin Wang
Hanlin Wang
Xiqing Zuo
Chao Xu

Miniature amphibious robots are capable of performing various tasks in complex terrestrial and aquatic environments due to their superior adaptability. However, the mobility of existing miniature amphibious robots in such environments is limited by their complex locomotion systems and single mode of motion. This work presents a novel insect-scale amphibious robot, powered by a single piezoelectric actuator. The prototype of the robot is fabricated and preliminarily tested preliminarily. By exploiting the different vibration modes of the piezoelectric actuators, the robot achieves movement in an amphibious environment. The robot employs the acoustic flow generated by the higher-order mode to achieve rapid motion at the water surface. In addition, the robot attains forward and backward motion on the ground by means of friction force between the driving feet and the ground. The findings of this study offer significant insights into the development of amphibious robots that exhibit enhanced flexibility and adaptability. These insights lay the foundation for the future applications of such robots in narrow amphibious settings.

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IJCAI Conference 2023 Conference Paper

Explainable Text Classification via Attentive and Targeted Mixing Data Augmentation

Songhao Jiang
Yan Chu
Zhengkui Wang
Tianxing Ma
Hanlin Wang
Wenxuan Lu
Tianning Zang
Bo Wang

Mixing data augmentation methods have been widely used in text classification recently. However, existing methods do not control the quality of augmented data and have low model explainability. To tackle these issues, this paper proposes an explainable text classification solution based on attentive and targeted mixing data augmentation, ATMIX. Instead of selecting data for augmentation without control, ATMIX focuses on the misclassified training samples as the target for augmentation to better improve the model's capability. Meanwhile, to generate meaningful augmented samples, it adopts a self-attention mechanism to understand the importance of the subsentences in a text, and cut and mix the subsentences between the misclassified and correctly classified samples wisely. Furthermore, it employs a novel dynamic augmented data selection framework based on the loss function gradient to dynamically optimize the augmented samples for model training. In the end, we develop a new model explainability evaluation method based on subsentence attention and conduct extensive evaluations over multiple real-world text datasets. The results indicate that ATMIX is more effective with higher explainability than the typical classification models, hidden-level, and input-level mixup models.

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ICRA Conference 2020 Conference Paper

A Fast, Accurate, and Scalable Probabilistic Sample-Based Approach for Counting Swarm Size

Hanlin Wang
Michael Rubenstein

This paper describes a distributed algorithm for computing the number of robots in a swarm, only requiring communication with neighboring robots. The algorithm can adjust the estimated count when the number of robots in the swarm changes, such as the addition or removal of robots. Probabilistic guarantees are given, which show the accuracy of this method, and the trade-off between accuracy, speed, and adaptability to changing numbers. The proposed approach is demonstrated in simulation as well as a real swarm of robots.

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IROS Conference 2020 Conference Paper

Automatic Control Synthesis for Swarm Robots from Formation and Location-based High-level Specifications

Ji Chen
Hanlin Wang
Michael Rubenstein
Hadas Kress-Gazit

In this paper, we propose an abstraction that captures high-level formation and location-based swarm behaviors, and an automated control synthesis framework to generate correct-by-construction behaviors. Our abstraction includes symbols representing both possible formations and physical locations in the workspace. We allow users to write linear temporal logic (LTL) specifications over the symbols to specify high-level tasks for the swarm. To satisfy a specification, we automatically synthesize a centralized symbolic plan, and environment and swarm-size-dependent motion controllers that are guaranteed to implement the symbolic transitions. In addition, using integer programming (IP), we assign robots to different sub-swarms to execute the synthesized symbolic plan. Our framework gives insights into controlling a large fleet of autonomous robots to achieve complex tasks which require composition of behaviors at different locations and coordination among different groups of robots in a correct-by-construction way. We demonstrate the proposed framework in simulation with 16 UAVs and 8 ground vehicles, and on a physical platform with 20 ground robots, showcasing the generality of the approach and discussing the implications of controlling constrained physical hardware.

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IROS Conference 2019 Conference Paper

Efficient and Guaranteed Planar Pose Graph optimization Using the Complex Number Representation

Taosha Fan
Hanlin Wang
Michael Rubenstein
Todd D. Murphey

In this paper, we present CPL-Sync, a certifiably correct algorithm to solve planar pose graph optimization (PGO) using the complex number representation. We formulate planar PGO as the maximum likelihood estimation (MLE) on the product of unit complex numbers, and relax this nonconvex quadratic complex optimization problem to complex semidefinite programming (SDP). Furthermore, we simplify the corresponding semidefinite programming to Riemannian staircase optimization (RSO) on complex oblique manifolds that can be solved with the Riemannian trust region (RTR) method. In addition, we prove that the SDP relaxation and RSO simplification are tight as long as the noise magnitude is below a certain threshold. The efficacy of this work is validated through comparisons with existing methods as well as applications on planar PGO in simultaneous localization and mapping (SLAM), which indicates that the proposed algorithm is capable of solving planar PGO certifiably, and is more efficient in numerical computation and more robust to measurement noises than existing state-of-the-art methods. The C++ code for CPL-Sync is available at https://github.com/fantaosha/CPL-Sync.

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IROS Conference 2016 Conference Paper

Autonomous mobile robot with independent control and externally driven actuation

Hanlin Wang
Michael Rubenstein

Complexity, cost, and power requirements for actuation of individual robots are large factors in limiting the size of robotic swarms. Here we present a prototype robotic system that allows for externally powered motion in 2D without sacrificing individual autonomy, which simplifies the robot hardware, possibly enabling larger swarm sizes. This is accomplished using a table surface that is moving in an orbital fashion, and where robots can move to any point on the table surface simply through a series of carefully timed attachment and detachment steps. We present a model for the robot's motion, and use this model to create a motion controller that allows the robot to move from its current position to any other position on the table in approximately a straight line. We show this controller working in simulation as well as on an experimental hardware system.

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