Aiguo Song

Southeast University (China) | SEU

The advent of cloud computing, 5G, and artificial intelligence technology has spurred the exponential growth of big data and the need for data compression. To alleviate the CPU burden, computational engines for data compression integrated into network cards and storage devices, giving rise to computational storage. However, computational storage fa...

This letter proposes a novel human-robot co-adaptation framework for robust and accurate user intent recognition, specifically in the context of automatic control in assistance robots such as neural prosthetics and rehabilitation devices empowered by electrophysiological signals. Our goal is to incorporate user adaptability early in the training ph...

With the development of virtual reality, the practical requirements of the wearable haptic interface have been greatly emphasized. While passive haptic devices are commonly used in virtual reality, they lack generality and are difficult to precisely generate continuous force feedback to users. In this work, we present SmartSpring, a new solution fo...

While robotic tactile sensors have been developed to help robots to perceive and interact effectively with their surrounding environment by mimicking the structure and function of human skin, most of them overlook the role of near-contact behavior and data structure modeling in robotic perception, which limits robotic exploration capabilities. To a...

Recent years have witnessed great success of deep convolutional networks in sensor-based human activity recognition (HAR), yet their practical deployment remains a challenge due to the varying computational budgets required to obtain a reliable prediction. This paper focuses on adaptive inference from a novel perspective of signal frequency, which...

Imbalanced data is a major challenge in classification tasks. Most classification algorithms tend to be biased toward the samples in the majority class but fail to classify the samples in the minority class. Recently, ensemble learning, as a promising method, has been rapidly developed in solving highly imbalanced classification. However, the desig...

In recent years, underwater robots have been increasingly used in the maintenance of hydraulic structures. Underwater manipulators are essential devices that are used to carry out such maintenance tasks. For delicate repair operations such as fixing tiny cracks, most existing underwater manipulators face limitations in terms of size, accuracy, and...

Skin-slip provides crucial cues about the interaction state and surface properties. Currently, most skin-slip devices focus on two-dimensional tactile slip display and have limitations when displaying surface properties like bumps and contours. In this paper, a wearable fingertip device with a simple, effective, and low-cost design for three-dimens...

Electroencephalogram (EEG)-based emotion recognition has gradually become a research hotspot. However, the large distribution differences of EEG signals across subjects make the current research stuck in a dilemma. To resolve this problem, in this article, we propose a novel and effective method, Multi-Source Feature Representation and Alignment Ne...

For upper limb rehabilitation, the robot-assisted technique in combination with serious games requires well-specified training plans. For the best quality of the rehabilitation process, customized game levels for each user are desired, while it is labor-intensive to design and adjust game levels for different individuals. We work on generating trai...

Fabric-based pneumatic actuators (FPAs) are extensively employed in the design of lightweight and compliant soft wearable assistive gloves. However, conventional FPAs typically exhibit limited output force, thereby restricting the applications of such gloves. This paper presents the development of a novel honeycomb pneumatic actuator (HPA) construc...

This work reports an adaptive path-following controller for a multijoint snake robot (MSR) to improve the adaptability of the robot to the environment. The new strategy estimates the time-varying parameters of the system and the external interference to adjust the motion state of the robot in real time. Estimations are used to compensate for the jo...

Soft pneumatic gloves are a promising tool for assisting stroke patients with hand dysfunction in their rehabilitation and daily activities. However, current gloves have limited extension force output. This article presents a hybrid actuator that combines a silicone flexion actuator with an extension actuator made from shape memory alloy (SMA) spri...

Problem: Emergency triage faces multiple challenges, including limited medical resources and inadequate manual triage nurses, which cause incorrect triage, overcrowding in the emergency department (ED), and long patient waiting time. Objective: This paper aims to propose and validate an accurate and efficient artificial intelligence-based method...

The assist-as-needed (AAN) controller is effective in robot-assisted rehabilitation. However, variations of the engagement of subjects with fixed controller often lead to unsatisfying results. Therefore, adaptive AAN that adjusts control parameters based on individualized engagement is essential to enhance the training effect further. Nevertheless,...

Background and objective: Medical image visualization is an essential tool for conveying anatomical information. Ray-casting-based volume rendering is commonly used for generating visualizations of raw medical images. However, exposing a target area inside the skin often requires manual tuning of transfer functions or segmentation of original imag...

Human activity recognition (HAR) using wearable sensors is always a research hotspot in ubiquitous computing scenario, in which feature learning has played a crucial role. Recent years have witnessed outstanding success of contrastive learning in image data, which learns invariant representations by adding contrastive loss to the last layer of deep...

Although the electroencephalography (EEG) based brain–computer interface (BCI) has been successfully developed for rehabilitation and assistance, it is still challenging to achieve continuous control of a brain-actuated mobile robot system. In this study, we propose a continuous shared control strategy combining continuous BCI and autonomous naviga...

Driven by the shortage of qualified nurses and the increasing average age of the population, the ambient assisted living style using intelligent service robots and smart home systems has become an excellent choice to free up caregiver time and energy and provide users with a sense of independence. However, users’ unique environments and differences...

In order to enable intelligent robots to recognize unknown objects as accurately as human beings, object perception research is of great significance in service and industrial robot application scenarios. However, object perception using spectral measurements under few-shot learning usually leads to a poor result because of inadequate training samp...

The issue of electrocardiogram (ECG)‐based person identification has attracted intense research interests nowadays. Different than existing related researches that advocate accentuating useful information and attenuating noisy artefacts in sensor data processing, A novel strategy of ‘turning waste into wealth’ is proposed to exploit the new discrim...

During recent years, channel attention has attracted great interest in deep learning community. Despite significant success, it has been rarely exploited in ubiquitous human activity recognition (HAR) scenario. To decrease computational overhead, the channel attention often uses global averaging pooling (GAP) to compress each channel into a simple...

Robotic manipulators are nowadays widely used in various underwater scenarios, but their motion control remains a challenging task due to hydrodynamic effects. This article proposes a novel adaptive fuzzy sliding mode control (AFSMC) strategy for precise and robust control of underwater manipulators. To simulate the movement of the robotic manipula...

Federated Learning (FL) has recently attracted great interest in sensor-based human activity recognition (HAR) tasks. However, in real-world environment, sensor data on devices is non-independently and identically distributed (Non-IID), e.g., activity data recorded by most devices is sparse, and sensor data distribution for each client may be incon...

Isopropyl alcohol molecules, as a biomarker for anti-virus diagnosis, play a significant role in the area of environmental safety and healthcare relating volatile organic compounds. However, conventional gas molecule detection exhibits dramatic drawbacks, like the strict working conditions of ion mobility methodology and weak light-matter interacti...

This letter presents a snake robot with a gripper for inspection and maintenance in narrow spaces. The proposed robot has a gripper equipped with a camera and a laser distance sensor that can inspect the surroundings and grasp objects. The control methods of the proposed robot consist of three parts: (1) A double-layer controller based on central p...

Stroke patients often suffer from poor motor function recovery due to a lack of good rehabilitation training. And hand function impairments especially affect daily life. To enable stroke patients to perform rehabilitation training safely and effectively on their own, we have designed a soft pneumatic robotic system for application in active hand re...

In order to realize the quantitative analysis and research of traditional Chinese medicine (TCM) acupuncture manipulations, miniaturized multi-dimensional force sensors are necessary to measure the lifting-thrusting force and twisting torque in the process of acupuncture, which records the manipulations of excellent physicians for relevant physicia...

The cuffless blood pressure (BP) monitoring device has attracted much attention because of its comfortable and real‐time monitoring. Inspired by the physical structure of the human epidermis, an ultra‐sensitive flexible resistive sensor with a double strain layer and crack structure is prepared by screen printing in this study. The strain material...

This paper investigates the state prediction problems for uncertain Euler–Lagrange systems with large time delays during data transmissions. A set of sequential predictors is proposed to estimate the actual real-time states of the systems by using the delayed information of measurements. The arbitrarily large delays are handled by applying adequate...

In this paper, a novel transformable leg-wheel mechanism is proposed. It has three active joints, among which the hip roll joint is directly driven, the hip pitch joint is driven by gear transmission, and the knee joint is driven by synchronous belt transmission. All the actuators are mounted on the body to reduce the weight of the leg-wheel mechan...

The growing and aging of the world population have driven the shortage of medical resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid development of robotics and artificial intelligence technologies help to adapt to the challenges in the healthcare field. Among them, intelligent speech technology (IST) has ser...

Background and objective: Artificial intelligence (AI) is widely applied in medical decision support systems. AI also plays an essential role in snakebite identification (SI). To date, no review has been conducted on AI-based SI. This work aims to identify, compare, and summarize the state-of-the-art AI methods in SI. Another objective is to analy...

Purpose The prerequisite for most traditional visual simultaneous localization and mapping (V-SLAM) algorithms is that most objects in the environment should be static or in low-speed locomotion. These algorithms rely on geometric information of the environment and restrict the application scenarios with dynamic objects. Semantic segmentation can b...

Humanoid tactility has been boosting robotic intelligence in object recognition, dexterous manipulation, and human–robot interaction. For many artificial tactile sensors, especially those based on optical principles, inflexibility, bulkiness, and monomodality limit their potential to function as humanoid skins. Herein, by embedding lab‐made optical...

Currently there still remains a critical need of human involvements for multi-robot system (MRS) to successfully perform their missions in real-world applications, and the hand-controller has been commonly used for the operator to input MRS control commands. However, in more challenging scenarios involving concurrent MRS control and system monitori...

The current “deep learning + large-scale data + strong supervised labeling” technology framework of collision avoidance for ground robots and aerial drones is becoming saturated. Its development gradually faces challenges from real open-scene applications, including small data, weak annotation, and cross-scene. Inspired by the neural structure and...

For intelligent surveillance, the issue of person re-identification has attracted extensive research interest due to its great academic value and broad application prospect. This issue aims to build the correspondence between human appearances across deployed non-overlapping cameras. However, the captured human images are inevitably influenced and...

Due to the non-standardization and complexity of the farmland environment, it is always a huge challenge for tractors to achieve fully autonomy (work at Self-driving mode) all the time in agricultural industry. Whereas, when tractors work in the Tele-driving (or Remote driving) mode, the operators are prone to fatigue because they need to concentra...

Credit assignment is a critical problem in cooperative Multi-Agent Reinforcement Learning (MARL). To address this problem, current studies mainly rely on the intrinsic reward, which is directly summed with the global reward to generate a total reward. However, such kinds of intrinsic reward functions ignore the dependence among agents and inevitabl...

Overhead aluminum conductor composite core (ACCC) transmission lines are extensively used. However, internal defects of ACCC wires are difficult to detect, threatening the stability and security of the grid. Thus, a novel automatic detection system using an X-ray inspection robot and an anchor-free object detection model is proposed to solve the pr...

In recent years, there has been a growing research interest in using deep learning to resolve the issue of Electroencephalogram (EEG)-based emotion recognition. Current research emphasizes exploiting the useful information from each single EEG channel or each individual set of multi-channel EEG, but overlooks the correlation information among diffe...

Despite strong representation ability, deep convolutional neural networks (CNNs) are largely hindered in practical human activity recognition (HAR) deployment due to high computational cost, which is often unaffordable on resource-limited wearable devices. In this paper, to bridge the gap between on-device HAR and deep learning, we present a collab...

Given the shortcomings of subjectivity and destructiveness associated with traditional methods of measuring food texture parameters (such as fruit firmness and meat tenderness) when using a texture meter, a non-contact measurement method utilizing an Air-puff combined with Structured Light Imaging (ASLI) was proposed in this study. First, the finit...

The tendon-sheath system (TSS) has emerged as a promising solution for force transmission in robot applications, owing to the lightweight, low inertia, and good flexibility. However, the performance of tension control is affected by the configuration-dependent nonlinearities, and achieving precise control of the distal force of TSS in time-varying...

Node positioning is an essential function of wireless networks and serves as the foundation for many applications. In the existing works, the cooperative positioning approaches have been extensively studied and are shown to be effective for scenarios with energy and cost constraints. However, these approaches may not perform well in concave network...

The multi-dimensional force/torque decoupling and calibration is extremely crucial to increase the accuracy of the Wheel Force Transducer/Sensor (WFT). A novel interpretable nonlinear decoupling and calibration approach to WFT is presented. A physical interpretable prime-error framework is developed such that the linear prime part accounts for most...

Objective: Electroencephalogram (EEG)-based emotion recognition is of great significance for aiding in clinical diagnosis, treatment, nursing and rehabilitation. Current research on this issue mainly focuses on utilizing various network architectures with different types of neurons to exploit the temporal, spectral, or spatial information from EEG...

Multi-Agent Reinforcement Learning (MARL) has made remarkable progress in recent years. However, in most MARL methods, agents share a policy or value network, which is easy to result in similar behaviors of agents and thus limits the flexibility of the method to handle complex tasks. To enhance the diversity of agent behaviors, we propose a novel m...

Currently, researchers incline to employ large-scale datasets as benchmarks for pre-training and fine-tuning models on small-scale datasets to achieve superior performance. However, many researchers cannot afford the enormous computational overhead that pre-training entails, and fine-tuning is easy to compromise the generalization ability of models...

This study investigates the trajectory tracking strategy of a snake robot with sideslip disturbance and unknown model parameters. To guide the robot to track the ideal trajectory faster and more accurately, an adaptive anti-sideslip strategy for a snake robot with the Integral Line-of-Sight (ILOS) function is reported. This technique eliminates dir...

Aiming at the problem of low recognition accuracy of motor imagery electroencephalogram signal due to individual differences of subjects, an individual adaptive feature representation method of motor imagery electroencephalogram signal is proposed in this paper. Firstly, based on the individual differences and signal characteristics in different fr...

Purpose This paper aims to present a fully actuated aerial manipulator (AM) with a robust motion/force hybrid controller for conducting contact-typed inspection tasks in industrial plants. Design/methodology/approach An AM is designed based on a hexarotor with tilted rotors and a rigidly attached end effector. By tilting the rotors, the position a...

The fractional differential algorithm has a good effect on extracting image textures, but it is usually necessary to select an appropriate fractional differential order for textures of different scales, so we propose a novel approach for haptic texture rendering of two-dimensional (2D) images by using an adaptive fractional differential method. Acc...

To respond to the rapid growth of shipping container throughput, terminals urgently need to improve the efficiency of thier operations and reduce operational costs through automation and intellectualization upgrades, thereby improving service levels and enhancing market competitiveness. Due to the advantages of reliable transportation, efficient op...

A novel concept—the contact-based landing on a mobile platform—is proposed in this paper. An adaptive backstepping controller is designed to deal with the unknown disturbances in the interactive process, and the contact-based landing mission is implemented under the hybrid force/motion control framework. A rotorcraft aerial vehicle system and a gro...

Flexible resistive sensors have attracted widespread attention in the field of wearable electronics. Inspired by the single-layer crack structure which has ultra-high sensitivity, a double strain layered crack structure is proposed to expand the maximum working strain (30%) of flexible sensor while maintaining the ultra-high sensitivity (GF = 2165...

Electromyography (EMG) generated by human hand movements is usually used to decode different action types with high accuracy. However, the classifications of the gestures rarely consider the impact of force, and the estimation of the grasp force when performing natural grasping movements is so far overlooked. Decoding natural grasping movements and...

This article presents a new aviation brain-computer interface, which includes the construction of a color brain power map and a cognitive detection network. The developed network, Bpmnet, can effectively detect the cognitive state of the brain. To improve the effectiveness of model parameter optimization algorithms, momentum and batch normalization...

Tissue retraction is an important task in head and neck surgery to leave space for surgical operations. Because the contact between the retractor and soft tissue is not trivial to model, the retraction operation has not been well addressed by robots in modern robot-assisted surgery. We propose a human-robot collaboration approach to assist the retr...