A ROS framework for the extrinsic calibration of intelligent vehicles: A multi-sensor, multi-modal approach

Oliveira, Miguel; Castro, Afonso; Madeira, Tiago; Pedrosa, Eurico; Dias, Paulo; Santos, Vítor

doi:10.1016/j.robot.2020.103558

Cited by 19 publications

(9 citation statements)

References 7 publications

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“…ATOM is a methodology that was proven to accurately calibrate several robotic systems. Additional details on the methodology itself are provided in [ 1 ], and usage cases of varied robotic systems can be read in [ 14 , 15 , 16 , 17 ]. This paper is focused not on the calibration methodology of ATOM, but rather on the support functionalities that create an integrated solution for the calibration of robotic systems.…”

Section: Related Workmentioning

confidence: 99%

“…Our previous work focused on the development of the Atomic Transformations Optimization Method’s (ATOM) calibration methodology. In particular, we worked on expanding the methodology for tackling hand–eye calibration problems [ 14 ], agricultural robots [ 15 ], autonomous vehicles [ 16 ] and collaborative cells [ 17 ]. In addition, we have shown several examples of successful calibrations [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

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ATOM Calibration Framework: Interaction and Visualization Functionalities

Gomes

Oliveira

Santos

2023

Sensors

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Robotic systems are evolving to include a large number of sensors and diverse sensor modalities. In order to operate a system with multiple sensors, the geometric transformations between those sensors must be accurately estimated. The process by which these transformations are estimated is known as sensor calibration. Behind every sensor calibration approach is a formulation and a framework. The formulation is the method by which the transformations are estimated. The framework is the set of operations required to carry out the calibration procedure. This paper proposes a novel calibration framework that gives more flexibility, control and information to the user, enhancing the user interface and the user experience of calibrating a robotic system. The framework consists of several visualization and interaction functionalities useful for a calibration procedure, such as the estimation of the initial pose of the sensors, the data collection and labeling, the data review and correction and the visualization of the estimation of the extrinsic and intrinsic parameters. This framework is supported by the Atomic Transformations Optimization Method formulation, referred to as ATOM. Results show that this framework is applicable to various robotic systems with different configurations, number of sensors and sensor modalities. In addition to this, a survey comparing the frameworks of different calibration approaches shows that ATOM provides a very good user experience.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

ATOM Calibration Framework: Interaction and Visualization Functionalities

Gomes

Oliveira

Santos

2023

Sensors

Self Cite

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“…In [ 33 ], an optimization procedure is implemented which, in addition to estimate the poses of the sensors, also estimates the poses of the calibration patterns. This enables the definition of errors to be formulated using sensor to calibration pattern tandems, rather than the classic sensor to sensor pairwise combinations.…”

Section: Related Workmentioning

confidence: 99%

Multi-Sensor Extrinsic Calibration Using an Extended Set of Pairwise Geometric Transformations

Santos

Rato

Dias

et al. 2020

Sensors

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Systems composed of multiple sensors for exteroceptive perception are becoming increasingly common, such as mobile robots or highly monitored spaces. However, to combine and fuse those sensors to create a larger and more robust representation of the perceived scene, the sensors need to be properly registered among them, that is, all relative geometric transformations must be known. This calibration procedure is challenging as, traditionally, human intervention is required in variate extents. This paper proposes a nearly automatic method where the best set of geometric transformations among any number of sensors is obtained by processing and combining the individual pairwise transformations obtained from an experimental method. Besides eliminating some experimental outliers with a standard criterion, the method exploits the possibility of obtaining better geometric transformations between all pairs of sensors by combining them within some restrictions to obtain a more precise transformation, and thus a better calibration. Although other data sources are possible, in this approach, 3D point clouds are obtained by each sensor, which correspond to the successive centers of a moving ball its field of view. The method can be applied to any sensors able to detect the ball and the 3D position of its center, namely, LIDARs, mono cameras (visual or infrared), stereo cameras, and TOF cameras. Results demonstrate that calibration is improved when compared to methods in previous works that do not address the outliers problem and, depending on the context, as explained in the results section, the multi-pairwise technique can be used in two different methodologies to reduce uncertainty in the calibration process.

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“…However, due to the limitation of personnel efficiency, many works have been done to improve the integration of intelligent technology and verification [3]. A general approach integrated with the Robot Operating System (ROS) framework is proposed to solve the problem of extrinsic calibration of multiple sensors of varied modalities, which allows for the interactive positioning of sensors and labeling of data [4]. In addition, B.A.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Temperature Verification System Based on Robotic Arm

Qiu

Yang

Huang

et al. 2022

J. Phys.: Conf. Ser.

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The key issue of meteorological temperature verification is how to operate itself without personnel deployment. This paper presents a meteorological temperature verification system based on robotic arm. Its goal is to realize the automatically operating by integrating robotic arm controller and verification software. The device level provides temperature verification instruments and the robotic arm. The communication function such as cyclic measurement of the resistance of temperature sensor, verification environmental data communication and temperature generator control can be realized by networking level. The interactive level ensures stable operation and fault location. Some key methods such as the system layout, the system workflow and the system integration method are also illustrated for system implementation.

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A ROS framework for the extrinsic calibration of intelligent vehicles: A multi-sensor, multi-modal approach

Cited by 19 publications

References 7 publications

ATOM Calibration Framework: Interaction and Visualization Functionalities

ATOM Calibration Framework: Interaction and Visualization Functionalities

Multi-Sensor Extrinsic Calibration Using an Extended Set of Pairwise Geometric Transformations

Design and Implementation of Temperature Verification System Based on Robotic Arm

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