25 accepted papers
We present PiLoT, a unified framework that tackles UAV-based ego and target geo-localization. Conventional approaches rely on decoupled pipelines that fuse GNSS and Visual-Inertial Odometry (VIO) for ego-pose estimation, and active sensors like laser rangefinders for target localization. However, th
In complex environments, traditional path planning methods rely on manually defined models, requiring tedious adjustments under varying scenarios or constraints. They also suffer from unstable time overhead and exponentially increasing computational costs as environmental complexity grows. Deep lear…
The myoelectric gesture recognition technology based on wearable armbands provides a natural and portable solution for human-robot interaction (HRI). However, various interferences during practical interactions can severely degrade the recognition model's performance, leading to reduced interaction
Deep object pose estimators are notoriously overconfident. A grasping agent that both estimates the 6-DoF pose of a target object and predicts the uncertainty of its own estimate could avoid task failure by choosing not to act under high uncertainty. Even though object pose estimation improves and u
The significance of Temporal Knowledge Graphs (TKGs) in Artificial Intelligence (AI) lies in their capacity to incorporate time-dimensional information, support complex reasoning and prediction, optimize decision-making processes, enhance the accuracy of recommendation systems, promote multimodal da…
The success of 3D Gaussian splatting in 3D reconstruction has recently led to efforts to integrate it with SLAM systems. However, most existing research has focused on indoor tracking and mapping, while outdoor Gaussian SLAM methods still heavily rely expensive LiDAR sensor. To address these challen
Slip detection and control is critical to achieving stable grasping in robotics. However, accurate and robust slip detection and control remains a challenging task. This letter proposes a learning framework with contrastive learning and feature alignment to improve the accuracy of end-to-end slip de
We propose a novel method for aerial visual localization over low Level-of-Detail (LoD) city models. Previous wireframe-alignment-based method LoD-Loc [99] has shown promising localization results leveraging LoD models. However, LoD-Loc mainly relies on high-LoD (LoD3 or LoD2) city models, but the m…
Recently, significant advancements have been made in 3D Gaussian Splatting SLAM for dynamic environments. However, most existing methods primarily address active dynamic objects, such as people and vehicles, and fail to account for the impact of passive dynamic objects on localization and mapping. T
Multimodal image fusion aims to merge features from different modalities to create a comprehensively representative image. However, existing medical image fusion methods often struggle to handle noise generated during image acquisition, significantly diminishing their impact on visual quality. To ad…
Large language models (LLMs) encounter challenges such as hallucination and factual errors in knowledge-intensive tasks. One the one hand, LLMs sometimes struggle to generate reliable answers based on the black-box parametric knowledge, due to the lack of responsible knowledge. Moreover, fragmented…
We propose a new method named LoD-Loc for visual localization in the air. Unlike existing localization algorithms, LoD-Loc does not rely on complex 3D representations and can estimate the pose of an Unmanned Aerial Vehicle (UAV) using a Level-of-Detail (LoD) 3D map. LoD-Loc mainly achieves this goal…
Individual physiological differences constrain the cross-user application of joint angle estimation models based on surface electromyography (sEMG) signals. Current cross-user methods for myoelectric joint angle estimation often involve the use of angle or optical sensors, which increases the traini
This paper solves the problem of real-time 6-DoF object tracking from an RGB video. Prior optimization-based methods optimize the object pose by aligning the projected model to the image based on handcrafted features, which are prone to suboptimal solutions. Recent learning-based methods use neural…
Despite the remarkable advances in image matching and pose estimation, image-based localization of a camera in a temporally-varying outdoor environment is still a challenging problem due to huge appearance disparity between query and reference images caused by illumination, seasonal and structural c…
During open surgeries, surgeons use tactile palpation to form an understanding of the anatomy, including any underlying anatomical structures such as arteries or tumors. This letter explores methods for restoring this capability in the context of minimally invasive robot-assisted surgery. Previous w
In this work, we develop an approach for guiding robots to automatically localize and find the shapes of tumors and other stiff inclusions present in the anatomy. Our approach uses Gaussian processes to model the stiffness distribution and active learning to direct the palpation path of the robot. T…
Existing robots for multi-scale motion (MSM) are unsuitable for micro-surgery in deep surgical sites where miniaturization and traversal of often tortuous anatomical passageways is required. Also, new emerging surgical paradigms for natural orifice surgery and image-based diagnosis and guidance at t…
Palpation is a key diagnostic aid for physicians when looking for tissue abnormalities. This letter focuses on autonomous robotic palpation for locating regions of interest representing possible tumor locations or underlying anatomy (e.g., a hidden artery). Many approaches direct the robot to exhaus
During early and middle stance of level-ground walking, the ankle joint usually rotates passively due to the locomotion of human body. Based on this passive dynamics of human locomotion, we develop an energy-efficient torque controller with hierarchical structure for a robotic prosthesis. The low-le
Registering a surgical tool to an a priori model of the environment is an important first step in computer-aided surgery. In this paper we present an approach for simultaneous registration and stiffness mapping using blind exploration of flexible environments. During contact-based exploration of fle
Surgeons often manually palpate tissue or organs in order to find tumors or other anatomical structures. Information about organ geometry and tissue stiffness gained from palpation can also be extremely useful in robotic surgery for diagnosis, surgical guidance, and registration to other preoperativ
Multi-backbone continuum robots have been demonstrated to possess wrench sensing capabilities by measuring the actuation load on each backbone and then using elaborate statics models. The ability to sense forces of interaction allows these robots to also control their interaction with the environmen
One of the goals of computer-aided surgery is to register intraoperative data to preoperative model of the anatomy, and hence add complementary information that can facilitate the task of surgical navigation. In this context, mechanical palpation can reveal critical anatomical features such as arter
This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Five locomotion modes, including sitting, standing still, level-ground walking, ascending stairs, and descending stairs, are taken into consideration. The recognition is performed with locomotion informa…