18 accepted papers
To address the challenge of achieving both low drag and high maneuverability in complex water-filled pipeline environments, this study proposes a novel dual-spherical pipeline robot with integrated leak detection and mapping capabilities. A multi-objective optimization framework was established to s…
Large language models (LLMs) are increasingly used to simulate human behavior in social settings such as legal mediation, negotiation, and dispute resolution. However, it remains unclear whether these simulations reproduce the personality–behavior patterns observed in humans. Human personality, for
When exploring complex unknown environments, unmanned aerial vehicles (UAVs) often experience reduced efficiency and robustness due to unevenly distributed occlusions. This paper proposes an efficient hybrid autonomous exploration algorithm that adapts to environmental complexity, enabling effective…
Underwater and in-air environments exhibit distinct imaging characteristics, which should be carefully considered and effectively exploited for accurate depth estimation. In this work, we analyze the effectiveness of wavelength-dependent attenuation for underwater depth estimation and show that it i…
Psychology research has shown that humans are poor at estimating their performance on tasks, tending towards underconfidence on easy tasks and overconfidence on difficult tasks. We examine three LLMs, Llama-3-70B-instruct, Claude-3-Sonnet, and GPT-4o, on a range of QA tasks of varying difficulty, an…
Large Language Models (LLMs) are increasingly deployed in socially complex, interaction-driven tasks, yet their ability to mirror human behavior in emotionally and strategically complex contexts remains underexplored. This study assesses the behavioral alignment of personality-prompted LLMs in adver
Large language models (LLMs) can leak sensitive training data through memorization and membership inference attacks. Prior work has primarily focused on strong adversarial assumptions, including attacker access to entire samples or long, ordered prefixes, leaving open the question of how vulnerable…
High-speed ground robots moving on unstructured terrains generate intense high-frequency vibrations, leading to LiDAR scan distortions in Lidar-inertial odometry (LIO). Accurate and efficient undistortion is extremely challenging due to (1) rapid and non-smooth state changes during intense vibration
The sparse optical flow method is a fundamental task in computer vision. However, its reliance on the assumption of constant environmental brightness constrains its applicability in high dynamic range (HDR) scenes. In this study, we propose a novel approach aimed at transcending image color informat
This paper considers the problem of learning from multiple sets of inaccurate labels, which can be easily obtained from low-cost annotators, such as rule-based annotators. Previous works typically concentrate on aggregating information from all the annotators, overlooking the significance of data re…
In order to address the high complexity and low efficiency of amphibious propulsion systems, this paper proposes a novel variable wheel-propeller integrated mechanism for amphibious robots. By adjusting the blade pitch angle, it enables multiple motion modes, including rapid and stable movement on f…
More and more robots are required to adsorb or crawl on the 3D curved surface in order to assist humans in some dangerous or tedious tasks. Existing methods on curved surface are merely able to plan in 2.5D environment at best, limiting the applications of the robots. In this letter, we propose an e
The strong performance of neural networks typically hinges on the availability of extensive labeled data, yet acquiring ground-truth labels is often challenging. Instead, noisy supervisions from multiple sources, e.g., by multiple well-designed rules, are more convenient to collect. In this paper, w…
How to design an optimal wearable device for human movement recognition is vital to reliable and accurate human-machine collaboration. Previous works mainly fabricate wearable devices heuristically. Instead, this paper raises an academic question: can we design an optimization algorithm to optimize…
Recognizing places using Lidar in large-scale environments is challenging due to the sparse nature of point cloud data. In this letter we present BVMatch, a Lidar-based frame-to-frame place recognition framework, that is capable of estimating 2D relative poses. Based on the assumption that the groun
To obtain synchronized gait assistance, this paper presents a new delayless adaptive dual-oscillator (ADO) scheme to address the inherent delay issue. In the ADO structure, a new oscillator is coupled with the primitive one but the phase is adaptively feed-forward compensated. It’s remarkable that t…
In this study, a passive arm-support exoskeleton was designed to provide assistive aid for manufacturing workers. The exoskeleton has two operating states which can be altered using an unique ratchet bar mechanism with two blocks fixed on the ratchet bar. When the upper arm is elevated to the highes…
In this study, a human-chair model was developed as the basis for a wearable chair design. A prototype chair, HUST-EC, was fabricated and evaluated. Employing the optimization under an inner point penalty function, an optimized simulation of the operating mode with the lowest chair height was implem…