25 accepted papers
Object detection has long been dominated by traditional coordinate regression-based models, such as YOLO, DETR, and Grounding DINO. Although recent efforts have attempted to leverage MLLMs to tackle this task, they face challenges like low recall rate, duplicate predictions, coordinate misalignment,
Traditional policy learning methods in cooperative pursuit face fundamental challenges in biomimetic underwater robots, where long-horizon decision making, partial observability, and inter-robot coordination require both expressiveness and stability. To address these issues, a novel framework called…
Object referring aims to detect all objects in an image that match a given natural language description. We argue that a robust object referring model should be grounded, meaning its predictions should be both explainable and faithful to the visual content. Specifically, it should satisfy two key pr…
The development of bionic underwater robots has brought new vitality to ocean exploration. Motion control is crucial for the stability of underwater robots due to significant differences in flow field characteristics at various swimming speeds. This study focuses on vertical-plane motion and propose…
The semi-supervised medical image segmentation with a few annotated data can provide significant help in robot-assisted surgery. This step plays a pivotal role in identification of pathological regions, more appropriate planning of surgical procedures, and so on. In this work, we develop an evidence
Biological adhesion represents a remarkable evolutionary adaptation, as exemplified by remoras using dorsal suction cups for hitchhiking and octopuses employing independently controllable suction cups to adhere to complex surfaces. Therefore, this study focuses on the design, quantitative analysis,
Existing approaches of hand reconstruction predominantly adhere to a multi-stage framework, encompassing detection, left-right classification, and pose estimation. This paradigm induces redundant computation and cumulative errors. In this work, we propose HandOS, an end-to-end framework for 3D hand…
Multimodal task specification is essential for enhanced robotic performance, where Cross-modality Alignment enables the robot to holistically understand complex task instructions. Directly annotating multimodal instructions for model training proves impractical, due to the sparsity of paired multimo
Embodied visual tracking is a fundamental skill in Embodied AI, enabling an agent to follow a specific target in dynamic environments using only egocentric vision. This task is inherently challenging as it requires both accurate target recognition and effective trajectory planning under conditions o…
As a new-type underwater robot with outstanding motion performance and environmental friendliness, bionic robotic fish holds enormous potential in the field of ocean exploration. In practical application, it is a vital mission for underwater robots to accomplish efficient and stable autonomous recov
The event camera, a bio-inspired asynchronous triggered camera, offers promising prospects for fusion with frame-based cameras owing to its low latency and high dynamic range. However, calibrating stereo vision systems that incorporate both event- and frame-based cameras remains a significant challe
This paper investigates the event-triggered-based pursuing and surrounding control of a multi-robotic fish system. A distributed surrounding control framework is put forward to deploy the whole system and enclose the dynamic evader into a convex hull. In particular, distributed kinematics-based moti
This paper proposes a tightly-coupled visual-Doppler-Velocity-Log (visual-DVL) fusion method for underwater robot localization through integrating the velocity measurements from a DVL into a visual odometry (VO). Considering that employing the DVL measurements in dead-reckoning systems easily leads…
Manta-inspired robots have been increasingly applied in vision-based underwater tasks. However, owing to the refraction effect and motion coupling problem, their accurate target following control is still poorly understood. This letter proposes a vision-based underwater target following scheme for r
Many aquatic animals are able to leap out of water effortlessly, however, it is still exceedingly challenging for a swimming robot. Inspired by the fast-swimming mechanism of fish, in this letter, we develop an untethered high-speed swimming robot with the integration of high-frequency oscillation a
"Open World Object Detection (OWOD) is a challenging computer vision problem that requires detecting unknown objects and gradually learning the identified unknown classes. However, it cannot distinguish unknown instances as multiple unknown classes. In this work, we propose a novel OWOD problem call…
Simultaneous localization and mapping is an indispensable yet challenging direction for mobile robots. Attracted by 3D LiDAR with accurate depth information and robustness to illumination variations, many 3D LiDAR SLAM methods based on scan-to-map matching have been developed. However, there is a cr
Underwater visual localization is an essential technique for the autonomous operation of underwater robots. However, the unique underwater image characteristics, including refraction, sparse features, and severe noise, pose an enormous challenge to it. For addressing these issues, this paper propose…
This paper proposes a multi-objective visionbased navigation network for biomimetic underwater robots to cope with scientific observation, target selection, and obstacle avoidance in marine missions. Structurally, a stereo block attention module is first constructed to serially extract the channel a…
Among visual relocalization from a single RGB image, the scene coordinate regression (SCoRe) based on convolutional neural network (CNN) becomes prevailing, however, it is insufficient to extract invariant features under different viewpoints due to fixed geometric structures of CNN. In this letter,
Soft robots have been applied widely to various constrained scenarios due to the advantages over traditional rigid manipulators such as softness, deformability and adaptability to constrained surroundings. To make full use of this merit, this paper proposes a method that integrates collision detecti…
Guided refinement is a popular procedure of various image post-processing applications. It produces output image based on input and guided images. Input images are usually flawed estimates containing kinds of noises and outliers, which undermine the edge consistency between input and guided images.…
Object detection methods fall into two categories, i.e., two-stage and single-stage detectors. The former is characterized by high detection accuracy while the latter usually has a considerable inference speed. Hence, it is imperative to fuse their merits for a better accuracy vs. speed trade-off. T…
Temporal object detection has attracted significant attention, but most popular methods can not leverage the rich temporal information in video or robotic vision. Although many different algorithms have been developed for video detection task, real-time online approaches are frequently deficient. In…
In this paper, we design and build a power line inspection robot capable of hybrid operation modes. Specifically, the developed robot is able to land on the overhead ground wire (OGW) and to move as the climbing robot. When to negotiate obstacles, it can vertically take off the wire and fly over the…