A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

Ci, Wenyan

doi:10.3390/s16101704

Cited by 14 publications

(10 citation statements)

References 22 publications

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“…Note that (27) should be transformed to the foot frame and expressed with sensor measurements to find the preintegrated foot measurement. We manipulate (27) by multiplying Ψ to both sides and augmenting the measurements, leading to:…”

Section: A Measurement Modelmentioning

confidence: 99%

“…For foot velocity preintegration, we stress that R v in (28) can be approximated by the body velocity measurement obtained from a stereo vision with optical flow analysis as follows [27]:…”

Section: A Measurement Modelmentioning

confidence: 99%

“…Note that we can recover the depth of features thanks to a calibrated stereo camera. Unlike [27], STEP does not establish the objective function to compute the body velocity quickly. Instead, the direct linear transformation (DLT) [28] is exploited.…”

Section: A Measurement Modelmentioning

confidence: 99%

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STEP: State Estimator for Legged Robots Using a Preintegrated foot Velocity Factor

Kim¹,

Yu²,

Lee³

et al. 2022

Preprint

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We propose a novel state estimator for legged robots, STEP, achieved through a novel preintegrated foot velocity factor. In the preintegrated foot velocity factor, the usual non-slip assumption is not adopted. Instead, the end effector velocity becomes observable by exploiting the body speed obtained from a stereo camera. In other words, the preintegrated end effector's pose can be estimated. Another advantage of our approach is that it eliminates the necessity for a contact detection step, unlike the typical approaches. The proposed method has also been validated in harsh-environment simulations and real-world experiments containing uneven or slippery terrains.

show abstract

Section: A Measurement Modelmentioning

confidence: 99%

“…For foot velocity preintegration, we stress that R v in (28) can be approximated by the body velocity measurement obtained from a stereo vision with optical flow analysis as follows [27]:…”

Section: A Measurement Modelmentioning

confidence: 99%

See 1 more Smart Citation

STEP: State Estimator for Legged Robots Using a Preintegrated foot Velocity Factor

Kim¹,

Yu²,

Lee³

et al. 2022

Preprint

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show abstract

“…For this reason, the Kanade-Lucas-Tomasi algorithm was used to track the piece during image-based visual servoing (IBVS). The depth information is obtained from the known kinematics of the robot [55,56]. Kanade-Lucas-Tomasi algorithm was used to track the piece during image-based visual servoing (IBVS).…”

Section: Visual Servoingmentioning

confidence: 99%

Design and Construction of a Cost-Effective Didactic Robotic Arm for Playing Chess, Using an Artificial Vision System

2019

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This paper presents the design and construction of a robotic arm that plays chess against a human opponent, based on an artificial vision system. The mechanical design was an adaptation of the robotic arm proposed by the rapid prototyping laboratory FabLab RUC (Fabrication Laboratory of the University of Roskilde). Using the software Solidworks, a gripper with 4 joints was designed. An artificial vision system was developed for detecting the corners of the squares on a chessboard and performing image segmentation. Then, an image recognition model was trained using convolutional neural networks to detect the movements of pieces on the board. An image-based visual servoing system was designed using the Kanade–Lucas–Tomasi method, in order to locate the manipulator. Additionally, an Arduino development board was programmed to control and receive information from the robotic arm using Gcode commands. Results show that with the Stockfish chess game engine, the system is able to make game decisions and manipulate the pieces on the board. In this way, it was possible to implement a didactic robotic arm as a relevant application in data processing and decision-making for programmable automatons.

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“…The concept of temporal flow [2] restricts the uncertainty to reduce error propagation from matches. A more direct way is careful feature selection and tracking, for example, ORB based [3], KLT based [4], and AKAZE based [5].…”

Section: Related Workmentioning

confidence: 99%

Image Antiblurring and Statistic Filter of Feature Space Displacement: Application to Visual Odometry for Outdoor Ground Vehicle

Zhao

Min

et al. 2018

Journal of Sensors

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Precise, reliable, and low-cost vehicular localization across a continuous spatiotemporal domain is an important problem in the field of outdoor ground vehicles. This paper proposes a visual odometry algorithm, where an ultrarobust and fast feature-matching scheme is combined with an effective antiblurring frame selection strategy. Our method follows the procedure of finding feature correspondences from consecutive frames and minimizing their reprojection error. The blurred image is a great challenge for localization with a sharp turn or fast movement. So we attempt to mitigate the impact of blur with an image singular value decomposition antiblurring algorithm. Moreover, a statistic filter of feature space displacement and circle matching are proposed to screen or prune potential matching features, so as to remove the outliers caused by mismatching. An evaluation of benchmark dataset KITTI and real outdoor data, with blur, low texture, and illumination change, demonstrates that the proposed ego-motion scheme significantly achieved performance with respect to the other state-of-the-art visual odometry approaches to a certain extent.

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A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

Cited by 14 publications

References 22 publications

STEP: State Estimator for Legged Robots Using a Preintegrated foot Velocity Factor

STEP: State Estimator for Legged Robots Using a Preintegrated foot Velocity Factor

Design and Construction of a Cost-Effective Didactic Robotic Arm for Playing Chess, Using an Artificial Vision System

Image Antiblurring and Statistic Filter of Feature Space Displacement: Application to Visual Odometry for Outdoor Ground Vehicle

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