Author name cluster

Guodong Lu

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5 papers

2 author rows

EAAI Journal 2025 Journal Article

A lightweight and robust detection network for diverse glass surface defects via scale- and shape-aware feature extraction

Huan Yu
Jin Wang
Jingru Yang
Yiming Liang
Zhihui Li
Zhan Wang
Haiyan He
Xusheng Zhang

As glass usage expands across industries, intelligent glass defect detection is essential for ensuring quality. However, the varying shapes and sizes of defects, coupled with numerous subtle defects and the demand for efficient detection, present challenges for existing methods in achieving both accurate and real-time detection. To address these, we propose the lightweight and robust Glass Surface Defect Network (GSDNet) via scale- and shape-aware feature extraction. Specifically, the novel Shape-aware Feature Extraction (SFE) block, which employs deformable convolution with special linear shape-adaptive offset constraints, forms the feature extraction network, enabling the adaptive extraction of local features for defects with irregular shapes. Meanwhile, the Scale-aware (SA) attention is proposed, incorporating spatial attention mechanism to guide the model in focusing on key features across different receptive fields, enhancing defect detection at various scales. Finally, to enhance detection efficiency, the Efficient Bidirectional Path Aggregation Network (EBiPAN) is proposed as the feature aggregation module, integrating high-resolution information through bi-directional concatenation to improve small defect detection while avoiding significant additional computational burden. To validate the effectiveness of GSDNet, we compile the first multi-class glass defect dataset, covering 4 types of glass and 12 defect categories. Extensive experiments demonstrate GSDNet exhibits exceptional accuracy and robustness, consistently outperforming 9 advanced networks, with a 6. 8% improvement in mean Average Precision and a notable 10. 9% improvement in mean Average Precision small over the You Only Look Once version 8. Moreover, the optimal balance of accuracy and efficiency is achieved, with a detection speed of 68 frames per second. The dataset and code are publicly available at: https: //github. com/FisherYuuri/GSDNet.

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NeurIPS Conference 2025 Conference Paper

Jury-and-Judge Chain-of-Thought for Uncovering Toxic Data in 3D Visual Grounding

Kaixiang Huang
Qifeng Zhang
Jin Wang
Jingru Yang
Yang Zhou
Huan Yu
Guodong Lu
Shengfeng He

3D Visual Grounding (3DVG) faces persistent challenges due to coarse scene-level observations and logically inconsistent annotations, which introduce ambiguities that compromise data quality and hinder effective model supervision. To address these challenges, we introduce Refer-Judge, a novel framework that harnesses the reasoning capabilities of Multimodal Large Language Models (MLLMs) to identify and mitigate toxic data. At the core of Refer-Judge is a Jury-and-Judge Chain-of-Thought paradigm, inspired by the deliberative process of the judicial system. This framework targets the root causes of annotation noise: jurors collaboratively assess 3DVG samples from diverse perspectives, providing structured, multi-faceted evaluations. Judges then consolidate these insights using a Corroborative Refinement strategy, which adaptively reorganizes information to correct ambiguities arising from biased or incomplete observations. Through this two-stage deliberation, Refer-Judge significantly enhances the reliability of data judgments. Extensive experiments demonstrate that our framework not only achieves human-level discrimination at the scene level but also improves the performance of baseline algorithms via data purification. Code is available at https: //github. com/Hermione-HKX/Refer_Judge.

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IROS Conference 2024 Conference Paper

Multistable Soft Actuator for Physical Human-robot Interaction

Juncai Long
Jituo Li
Xiaojie Diao
Chengdi Zhou
Guodong Lu
Yixiong Feng

Collaboration with robots through physical contact offers a more intuitive, natural, and engaging operational experience, showcasing vast potential in the field of human-robot interaction. However, current physical interaction devices, such as collaborative robots and haptic feedback mechanisms, are limited by their singular modes of motion and feedback, hindering enhancements in interaction experiences. Herein, we present a multistable soft actuator capable of driving multimodal shape changes and passively conforming to user touch. This actuator can memorize and maintains any deformation with zero power consumption. Its structural mechanical properties can be dynamically adjusted to produce rich haptic feedback for the user, including changes in shape, elasticity, stiffness, and even sensations of rupture and weightlessness. Structurally, the mechanism consists of a network of pneumatic bistable units in series and parallel configurations, which can switch states under air pressure or external force, achieving extension, contraction, and omnidirectional bending. The input of air pressure can either impede or assist deformation, altering structural stiffness and resulting in varied loading curves. With its high safety in physical interactions, robust operability, and rich mechanical tactile feedback, the multistable soft actuator promises new design directions for physical human-robot interaction devices.

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IROS Conference 2024 Conference Paper

Under-actuated Robotic Gripper with Multiple Grasping Modes Inspired by Human Finger

Jihao Li
Tingbo Liao
Hassen Nigatu
Haotian Guo
Guodong Lu
Huixu Dong

Under-actuated robot grippers, as a pervasive tool of robots, have become a considerable research focus. Despite their simplicity of mechanical design and control strategy, they suffer from poor versatility and weak adaptability, making widespread applications limited. To better address relevant research gaps, we present a novel 3-finger linkage-based gripper that realizes retractable and reconfigurable multi-mode grasps driven by a single motor. Firstly, inspired by the changes occurred in the contact surface with a human finger moving, we artfully design a slider-slide rail mechanism as the phalanx to achieve retraction of each finger, allowing for better performance in the enveloping grasping mode. Secondly, a reconfigurable structure is constructed to broaden the grasping range of objects’ dimensions for the proposed gripper. By adjusting the configuration and gesture of each finger, the gripper can achieve five grasping modes. Thirdly, the proposed gripper is solely actuated by a single motor, yet it can be capable of grasping and reconfiguring simultaneously. Finally, various experiments on grasps of slender, thin, and large-volume objects are implemented to evaluate the performance of the proposed gripper in practical scenarios, which demonstrates the excellent grasping capabilities of the gripper.

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IROS Conference 2023 Conference Paper

Roller-Quadrotor: A Novel Hybrid Terrestrial/Aerial Quadrotor with Unicycle-Driven and Rotor-Assisted Turning

Zhi Zheng
Jin Wang 0015
Yuze Wu
Qifeng Cai
Huan Yu 0002
Ruibin Zhang
Jie Tu
Jun Meng

The Roller-Quadrotor is a novel quadrotor that combines the maneuverability of aerial drones with the endurance of ground vehicles. This work focuses on the design, modeling, and experimental validation of the Roller-Quadrotor. Flight capabilities are achieved through a quadrotor config-uration, with four thrust-providing actuators. Additionally, rolling motion is facilitated by a unicycle-driven and rotor-assisted turning structure. By utilizing terrestrial locomotion, the vehicle can overcome rolling and turning resistance, thereby conserving energy compared to its flight mode. This innovative approach not only tackles the inherent challenges of traditional rotorcraft but also enables the vehicle to roll through narrow gaps and overcome obstacles by taking advantage of its aerial mobility. We develop comprehensive models and controllers for the Roller-Quadrotor and validate their performance through experiments. The results demonstrate its seamless transition between aerial and terrestrial locomotion, as well as its ability to safely roll through gaps half the size of its diameter. Moreover, the terrestrial range of the vehicle is approximately 2. 8 times greater, while the operating time is about 41. 2 times longer compared to its aerial capabilities. These findings underscore the feasibility and effectiveness of the proposed structure and control mechanisms for efficient rolling through challenging terrains while conserving energy.

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