High-precision visual navigation device calibration method based on collimator
College of Aerospace Science and Engineering, National University of Defense Technology（国防科技大学航天科学与工程学院）；North Navigation Control Technology Co., Ltd（北方导航控制技术股份有限公司）
Visual navigation devices require precise calibration to achieve high-precision localization and navigation, which includes camera and attitude calibration. To address the limitations of time-consuming camera calibration and complex attitude adjustment processes, this study presents a collimator-based calibration method and system. Based on the optical characteristics of the collimator, a single-image camera calibration algorithm is introduced. In addition, integrated with the precision adjustment mechanism of the calibration frame, a rotation transfer model between coordinate systems enables efficient attitude calibration. Experimental results demonstrate that the proposed method achieves accuracy and stability comparable to traditional multi-image calibration techniques. Specifically, the re-projection errors are less than 0.1463 pixels, and average attitude angle errors are less than 0.0586 degrees with a standard deviation less than 0.0257 degrees, demonstrating high precision and robustness.
Institute of Industrial Science, The University of Tokyo（东京大学工业科学研究所）；Microsoft（微软）
Robot navigation technology is required to accomplish difficult tasks in various environments. In navigation, it is necessary to know the information of the external environments and the state of the robot under the environment. On the other hand, various studies have been done on SLAM technology, which is also used for navigation, but also applied to devices for Mixed Reality and the like. In this paper, we propose a robot-device calibration method for navigation with a device using SLAM technology on a robot. The calibration is performed by using the position and orientation information give…
The University of Sydney（悉尼大学）；The Australian Centre for Field Robotics（澳大利亚现场机器人中心）
Line scanning cameras, which capture only a single line of pixels, have been increasingly used in ground based mobile or robotic platforms. In applications where it is advantageous to directly georeference the camera data to world coordinates, an accurate estimate of the camera's 6D pose is required. This paper focuses on the common case where a mobile platform is equipped with a rigidly mounted line scanning camera, whose pose is unknown, and a navigation system providing vehicle body pose estimates. We propose a novel method that estimates the camera's pose relative to the navigation system.…
This work presents the most recent advances of the Robotic Testbed for Rendezvous and Optical Navigation (TRON) at Stanford University - the first robotic testbed capable of validating machine learning algorithms for spaceborne optical navigation. The TRON facility consists of two 6 degrees-of-freedom KUKA robot arms and a set of Vicon motion track cameras to reconfigure an arbitrary relative pose between a camera and a target mockup model. The facility includes multiple Earth albedo light boxes and a sun lamp to recreate the high-fidelity spaceborne illumination conditions. After the overview…
SurgNavAR: An Augmented Reality Surgical Navigation Framework for Optical See-Through Head Mounted Displays
Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine, Erasmus MC（鹿特丹伊拉斯姆斯大学医学中心放射与核医学系鹿特丹生物医学成像组）；Department of Oral and Maxillofacial Surgery, Erasmus MC（鹿特丹伊拉斯姆斯大学医学中心口腔颌面外科）；University of Groningen（格罗宁根大学）；Department of High Performance Compute & Visualization, SURF bv（SURF bv高性能计算与可视化部）；Department of Neurosurgery, Erasmus MC（鹿特丹伊拉斯姆斯大学医学中心神经外科）；Trauma Research Unit, Department of Surgery, Erasmus MC（鹿特丹伊拉斯姆斯大学医学中心外科创伤研究单元）
University of California Berkeley（加州大学伯克利分校）；DSO National Laboratories（新加坡国防科技研究院）；National University of Singapore（新加坡国立大学）；Graz University of Technology（格拉茨技术大学）；ETH Zürich（苏黎世联邦理工学院）；Microsoft（微软）
Cameras are a crucial exteroceptive sensor for self-driving cars as they are low-cost and small, provide appearance information about the environment, and work in various weather conditions. They can be used for multiple purposes such as visual navigation and obstacle detection. We can use a surround multi-camera system to cover the full 360-degree field-of-view around the car. In this way, we avoid blind spots which can otherwise lead to accidents. To minimize the number of cameras needed for surround perception, we utilize fisheye cameras. Consequently, standard vision pipelines for 3D mappi…
DualVision ArthroNav: Investigating Opportunities to Enhance Localization and Reconstruction in Image-based Arthroscopy Navigation via External Cameras
University of Arkansas（阿肯色大学）；Arthrex Inc.（阿瑟克斯公司）
Hong Kong University of Science and Technology（香港科技大学）
Accurate state estimation is a fundamental module for various intelligent applications, such as robot navigation, autonomous driving, virtual and augmented reality. Visual and inertial fusion is a popular technology for 6-DOF state estimation in recent years. Time instants at which different sensors' measurements are recorded are of crucial importance to the system's robustness and accuracy. In practice, timestamps of each sensor typically suffer from triggering and transmission delays, leading to temporal misalignment (time offsets) among different sensors. Such temporal offset dramatically i…
The advances in deep reinforcement learning recently revived interest in data-driven learning based approaches to navigation. In this paper we propose to learn viewpoint invariant and target invariant visual servoing for local mobile robot navigation; given an initial view and the goal view or an image of a target, we train deep convolutional network controller to reach the desired goal. We present a new architecture for this task which rests on the ability of establishing correspondences between the initial and goal view and novel reward structure motivated by the traditional feedback control…
As cameras and inertial sensors are becoming ubiquitous in mobile devices and robots, it holds great potential to design visual-inertial navigation systems (VINS) for efficient versatile 3D motion tracking which utilize any (multiple) available cameras and inertial measurement units (IMUs) and are resilient to sensor failures or measurement depletion. To this end, rather than the standard VINS paradigm using a minimal sensing suite of a single camera and IMU, in this paper we design a real-time consistent multi-IMU multi-camera (MIMC)-VINS estimator that is able to seamlessly fuse multi-modal …
Electromagnetic Navigation for Femoral Osteotomy Using High-Accuracy X-ray-to-CT Registration
Department of Pediatric Orthopedics and Traumatology, University Children’s Hospital Zürich（苏黎世大学儿童医院小儿骨科与创伤外科部门）；Research in Orthopedic Computer Science, University Hospital Balgrist, University of Zurich（骨科计算机科学研究所，巴尔格里斯大学医院，苏黎世大学）；Department of Orthopedic Surgery, University Hospital Balgrist, University of Zurich（骨科外科部门，巴尔格里斯大学医院，苏黎世大学）
Mila（米拉研究所）；Universite de Montreal（蒙特利尔大学）；IIT Kanpur（印度理工学院坎普尔分校）；University of Toronto（多伦多大学）
Learning effective visuomotor policies for robots purely from data is challenging, but also appealing since a learning-based system should not require manual tuning or calibration. In the case of a robot operating in a real environment the training process can be costly, time-consuming, and even dangerous since failures are common at the start of training. For this reason, it is desirable to be able to leverage \textit{simulation} and \textit{off-policy} data to the extent possible to train the robot. In this work, we introduce a robust framework that plans in simulation and transfers well to …
RASR: Range-Aware Scale Recovery for Metric UAV Navigation
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics（南京航空航天大学电子信息工程学院）；Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Noah Ark Lab, Huawei（华为诺亚方舟实验室）；College of Automation Engineering, Nanjing University of Aeronautics and Astronautics（南京航空航天大学自动化工程学院）；College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics（南京航空航天大学人工智能学院）；College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics（南京航空航天大学计算机科学与技术学院）
Observation Quality in DSM-Assisted Aerial Localization: A Benchmark and Base-Anchored Uncertainty Calibration
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息研究院）；School of Electronic Engineering, Beijing University of Posts and Telecommunications（北京邮电大学电子工程学院）
University of Calgary（卡尔加里大学）；Cumming School of Medicine（卡明医学院）；Curtin University（科廷大学）；School of Earth and Planetary Sciences（地球与行星科学学院）；Vusion Technologies（Vusion技术公司）；Schulich School of Engineering（舒立克工程学院）；Leica Geosystems（徕卡测量系统公司）；University of Alberta（阿尔伯塔大学）
Visual perception is regularly used by humans and robots for navigation. By either implicitly or explicitly mapping the environment, ego-motion can be determined and a path of actions can be planned. The process of mapping and navigation are delicately intertwined; therefore, improving one can often lead to an improvement of the other. Both processes are sensitive to the interior orientation parameters of the camera system and mathematically modelling these systematic errors can often improve the precision and accuracy of the overall solution. This paper presents an automatic camera calibratio…
Morphable design and depth-based visual control are two upcoming trends leading to advancements in the field of quadrotor autonomy. Stereo-cameras have struck the perfect balance of weight and accuracy of depth estimation but suffer from the problem of depth range being limited and dictated by the baseline chosen at design time. In this paper, we present a framework for quadrotor navigation based on a stereo camera system whose baseline can be adapted on-the-fly. We present a method to calibrate the system at a small number of discrete baselines and interpolate the parameters for the entire ba…
Polarimetric imaging has been applied in a growing number of applications in robotic vision (ex. underwater navigation, glare removal, de-hazing, object classification, and depth estimation). One can find on the market RGB Polarization cameras that can capture both color and polarimetric state of the light in a single snapshot. Due to the sensor's characteristic dispersion, and the use of lenses, it is crucial to calibrate these types of cameras so as to obtain correct polarization measurements. The calibration methods that have been developed so far are either not adapted to this type of came…
Advanced Research Lab, Navinfo Europe（四维图新欧洲高级研究实验室）
Spatial scene-understanding, including dense depth and ego-motion estimation, is an important problem in computer vision for autonomous vehicles and advanced driver assistance systems. Thus, it is beneficial to design perception modules that can utilize crowdsourced videos collected from arbitrary vehicular onboard or dashboard cameras. However, the intrinsic parameters corresponding to such cameras are often unknown or change over time. Typical manual calibration approaches require objects such as a chessboard or additional scene-specific information. On the other hand, automatic camera calib…
Motor Focus: Fast Ego-Motion Prediction for Assistive Visual Navigation
School of Computing, Clemson University（克莱姆森大学计算学院）；Stevens Institute of Technology（史蒂文斯理工学院）；School of Cultural and Social Studies, Tokai University（东海大学文化与社会研究学院）
Sensor calibration, which can be intrinsic or extrinsic, is an essential step to achieve the measurement accuracy required for modern perception and navigation systems deployed on autonomous robots. To date, intrinsic calibration models for spinning LiDARs have been based on hypothesized based on their physical mechanisms, resulting in anywhere from three to ten parameters to be estimated from data, while no phenomenological models have yet been proposed for solid-state LiDARs. Instead of going down that road, we propose to abstract away from the physics of a LiDAR type (spinning vs solid-stat…
