A Joint Extrinsic Calibration Tool for Radar, Camera and Lidar

Domhof, Joris; Kooij, Julian F. P.; Gavrila, Dariu M.

doi:10.1109/tiv.2021.3065208

Cited by 55 publications

(26 citation statements)

References 30 publications

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“…The design of MOSs is inspired by the widely-used operating systems, e.g., computer operating systems, robot operating systems [74], [75]. MoSs are essentially the blockchain-based human-machine interactive platforms comprised of a collection of program modules that control the running and operations of various hardware and software resources, e.g., network, data, models, algorithms, knowledge, incentive, etc.…”

Section: New Management Solution: Management Operating Systemsmentioning

confidence: 99%

The Future of Management: DAO to Smart Organizations and Intelligent Operations

Qin

Wang

2023

IEEE Trans. Syst. Man Cybern, Syst.

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In the future, management in smart societies will revolve around knowledge workers and the works they produce. This article is committed to explore new management framework, model, paradigm, and solution for organizing, managing, and measuring knowledge works. First, the parallel management framework is presented that would allow for the virtual-real interactions of humans in social space, robots in physical space, and digital humans in cyberspace to realize descriptive, predictive, and prescriptive intelligence for management. Then, the management foundation models are proposed by fusing scenarios engineering with artificial intelligence foundation models and cyber-physical-social systems. Moreover, the new management paradigm driven by decentralized autonomous organizations and operations is formulated for the advancement of smart organizations and intelligent operations. On these basis, the management operating systems that highlight features of simple intelligence, provable security, flexible scalability, and ecological harmony are finally put forward as new management solution.Index Terms-Decentralized autonomous organizations and operations (DAO), management foundation model, management intelligence, management operating system (MOS), metaverse, parallel management. I. INTRODUCTIONM ANAGEMENT is regarded as the art and science of how to effectively use resources to achieve the predefined goals. Management as a field originated from ancient China [1], [2], [3], [4] and dated from the monograph entitled "Guanzi" [5], [6], [7], which contains the dialectical idea of the opposition and unity between simplicity and complexity as well as many unique management concepts and thoughts. Especially, its decision-making concept is very Manuscript

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Section: New Management Solution: Management Operating Systemsmentioning

confidence: 99%

The Future of Management: DAO to Smart Organizations and Intelligent Operations

Qin

Wang

2023

IEEE Trans. Syst. Man Cybern, Syst.

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“…We recorded the output of the following sensors: a ZF FR-Gen21 3+1D radar (see Table II for specifications, ∼13 Hz) mounted behind the front bumper, a stereo camera (1936 × 1216 px, ∼30 Hz) mounted on the windshield, a Velodyne HDL-64 S3 LIDAR (∼10 Hz) scanner on the roof, and the ego vehicle's odometry (filtered combination of RTK GPS, IMU, and wheel odometry, ∼100 Hz). All sensors were jointly calibrated following [40]. See Fig.…”

Section: A Measurement Setup and Provided Datamentioning

confidence: 99%

Multi-Class Road User Detection With 3+1D Radar in the View-of-Delft Dataset

Palffy

Pool

Baratam

et al. 2022

IEEE Robot. Autom. Lett.

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123

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Next-generation automotive radars provide elevation data in addition to range-, azimuth-and Doppler velocity. In this experimental study, we apply a state-of-the-art object detector (PointPillars), previously used for LiDAR 3D data, to such 3+1D radar data (where 1D refers to Doppler). In ablation studies, we first explore the benefits of the additional elevation information, together with that of Doppler, radar cross section and temporal accumulation, in the context of multi-class road user detection. We subsequently compare object detection performance on the radar and LiDAR point clouds, object class-wise and as a function of distance. To facilitate our experimental study, we present the novel View-of-Delft (VoD) automotive dataset. It contains 8693 frames of synchronized and calibrated 64-layer LiDAR-, (stereo) camera-, and 3+1D radar-data acquired in complex, urban traffic. It consists of 123106 3D bounding box annotations of both moving and static objects, including 26587 pedestrian, 10800 cyclist and 26949 car labels. Our results show that object detection on 64-layer LiDAR data still outperforms that on 3+1D radar data, but the addition of elevation information and integration of successive radar scans helps close the gap. The VoD dataset is made freely available for scientific benchmarking at https://intelligent-vehicles.org/datasets/view-ofdelft/.

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“…These include automatic mutual information maximization schemes [22,30], edge alignment methods [34], and plane alignment methods [13,34]. These methods vary from being completely unstructured to using manufactured targets, such as standard planar checkerboards [33] or custom multi-modal targets [6]. Kang and Doh [17] propose a probabilistic edge detection method to maximize the detected edge overlap between lidar scans and images.…”

Section: Related Workmentioning

confidence: 99%

“…The location of the projected point, p, is then used to acquire the associated event activity in the accumulated event map image as shown in Eq. (6).…”

Section: Probability Distribution Formulationmentioning

confidence: 99%

L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras

Ta¹,

Bruggemann²,

Tim³

et al. 2022

Preprint

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Despite significant academic and corporate efforts, autonomous driving under adverse visual conditions still proves challenging. As neuromorphic technology has matured, its application to robotics and autonomous vehicle systems has become an area of active research. Low-light and latency-demanding situations can benefit. To enable event cameras to operate alongside staple sensors like lidar in perception tasks, we propose a direct, temporallydecoupled calibration method between event cameras and lidars. The high dynamic range and low-light operation of event cameras are exploited to directly register lidar laser returns, allowing information-based correlation methods to optimize for the 6-DoF extrinsic calibration between the two sensors. This paper presents the first direct calibration method between event cameras and lidars, removing dependencies on frame-based camera intermediaries and/or highly-accurate hand measurements. Code will be made publicly available.

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A Joint Extrinsic Calibration Tool for Radar, Camera and Lidar

Cited by 55 publications

References 30 publications

The Future of Management: DAO to Smart Organizations and Intelligent Operations

The Future of Management: DAO to Smart Organizations and Intelligent Operations

Multi-Class Road User Detection With 3+1D Radar in the View-of-Delft Dataset

L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras

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