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Yueri Cai
Robotics Institute, Beihang University, Beijing 100191, China

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Preprint content
Published: 16 July 2021
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ACS Style

Wei Sun; Jingjun Yu; Yueri Cai. Analysis and Study of Variable Stiffness Joints Based on Bi-Material Nested Elastomers. 2021, 1 .

AMA Style

Wei Sun, Jingjun Yu, Yueri Cai. Analysis and Study of Variable Stiffness Joints Based on Bi-Material Nested Elastomers. . 2021; ():1.

Chicago/Turabian Style

Wei Sun; Jingjun Yu; Yueri Cai. 2021. "Analysis and Study of Variable Stiffness Joints Based on Bi-Material Nested Elastomers." , no. : 1.

Review
Published: 27 April 2021 in Applied Sciences
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By moving a commercial 2D LiDAR, 3D maps of the environment can be built, based on the data of a 2D LiDAR and its movements. Compared to a commercial 3D LiDAR, a moving 2D LiDAR is more economical. A series of problems need to be solved in order for a moving 2D LiDAR to perform better, among them, improving accuracy and real-time performance. In order to solve these problems, estimating the movements of a 2D LiDAR, and identifying and removing moving objects in the environment, are issues that should be studied. More specifically, calibrating the installation error between the 2D LiDAR and the moving unit, the movement estimation of the moving unit, and identifying moving objects at low scanning frequencies, are involved. As actual applications are mostly dynamic, and in these applications, a moving 2D LiDAR moves between multiple moving objects, we believe that, for a moving 2D LiDAR, how to accurately construct 3D maps in dynamic environments will be an important future research topic. Moreover, how to deal with moving objects in a dynamic environment via a moving 2D LiDAR has not been solved by previous research.

ACS Style

Shusheng Bi; Chang Yuan; Chang Liu; Jun Cheng; Wei Wang; Yueri Cai. A Survey of Low-Cost 3D Laser Scanning Technology. Applied Sciences 2021, 11, 3938 .

AMA Style

Shusheng Bi, Chang Yuan, Chang Liu, Jun Cheng, Wei Wang, Yueri Cai. A Survey of Low-Cost 3D Laser Scanning Technology. Applied Sciences. 2021; 11 (9):3938.

Chicago/Turabian Style

Shusheng Bi; Chang Yuan; Chang Liu; Jun Cheng; Wei Wang; Yueri Cai. 2021. "A Survey of Low-Cost 3D Laser Scanning Technology." Applied Sciences 11, no. 9: 3938.

Article
Published: 01 September 2019 in Journal of Bionic Engineering
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This paper presents the design of a bionic pectoral fin with fin rays driven by multi-joint mechanism. Inspired by the cownose ray, the bionic pectoral fin is modeled and simplified based on the key structure and movement parameters of the cownose ray’s pectoral fin. A novel bionic propulsion fin ray composed of a synchronous belt mechanism and a slider-rocker mechanism is designed and optimized in order to minimize the movement errors between the designed fin rays and the spanwise curves observed from the cownose ray, and thereby reproducing an actively controllable flapping deformation. A bionic flapping pectoral fin prototype is developed accordingly. Observations verify that the bionic pectoral fin flaps consistently with the design rule extracted from the cownose ray. Experiments in a towing tank are set up to test its capability of generating the lift force and the propulsion force. The movement parameters within the usual propulsion capabilities of the bionic pectoral fin are utilized: The flapping frequency of 0.2 Hz–0.6 Hz, the flapping amplitude of 3°–18°, and the phase difference of 10°–60°. The results show that the bionic pectoral fin with actively controllable spatial deformation has expected propulsion performance, which supports that the natural features of the cownose ray play an important role in designing and developing a bionic prototype.

ACS Style

Yueri Cai; Lingkun Chen; Shusheng Bi; Guoyuan Li; Houxiang Zhang. Bionic Flapping Pectoral Fin with Controllable Spatial Deformation. Journal of Bionic Engineering 2019, 16, 916 -930.

AMA Style

Yueri Cai, Lingkun Chen, Shusheng Bi, Guoyuan Li, Houxiang Zhang. Bionic Flapping Pectoral Fin with Controllable Spatial Deformation. Journal of Bionic Engineering. 2019; 16 (5):916-930.

Chicago/Turabian Style

Yueri Cai; Lingkun Chen; Shusheng Bi; Guoyuan Li; Houxiang Zhang. 2019. "Bionic Flapping Pectoral Fin with Controllable Spatial Deformation." Journal of Bionic Engineering 16, no. 5: 916-930.

Journal article
Published: 13 February 2019 in Remote Sensing
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The state-of-the-art visual simultaneous localization and mapping (V-SLAM) systems have high accuracy localization capabilities and impressive mapping effects. However, most of these systems assume that the operating environment is static, thereby limiting their application in the real dynamic world. In this paper, by fusing the information of an RGB-D camera and two encoders that are mounted on a differential-drive robot, we aim to estimate the motion of the robot and construct a static background OctoMap in both dynamic and static environments. A tightly coupled feature-based method is proposed to fuse the two types of information based on the optimization. Dynamic pixels occupied by dynamic objects are detected and culled to cope with dynamic environments. The ability to identify the dynamic pixels on both predefined and undefined dynamic objects is available, which is attributed to the combination of the CPU-based object detection method and a multiview constraint-based approach. We first construct local sub-OctoMaps by using the keyframes and then fuse the sub-OctoMaps into a full OctoMap. This submap-based approach gives the OctoMap the ability to deform, and significantly reduces the map updating time and memory costs. We evaluated the proposed system in various dynamic and static scenes. The results show that our system possesses competitive pose accuracy and high robustness, as well as the ability to construct a clean static OctoMap in dynamic scenes.

ACS Style

Dongsheng Yang; Shusheng Bi; Wei Wang; Chang Yuan; Xianyu Qi; Yueri Cai. DRE-SLAM: Dynamic RGB-D Encoder SLAM for a Differential-Drive Robot. Remote Sensing 2019, 11, 380 .

AMA Style

Dongsheng Yang, Shusheng Bi, Wei Wang, Chang Yuan, Xianyu Qi, Yueri Cai. DRE-SLAM: Dynamic RGB-D Encoder SLAM for a Differential-Drive Robot. Remote Sensing. 2019; 11 (4):380.

Chicago/Turabian Style

Dongsheng Yang; Shusheng Bi; Wei Wang; Chang Yuan; Xianyu Qi; Yueri Cai. 2019. "DRE-SLAM: Dynamic RGB-D Encoder SLAM for a Differential-Drive Robot." Remote Sensing 11, no. 4: 380.

Journal article
Published: 14 September 2018 in Sensors
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This paper simultaneously calibrates odometry parameters and the relative pose between a monocular camera and a robot automatically. Most camera pose estimation methods use natural features or artificial landmark tools. However, there are mismatches and scale ambiguity for natural features; the large-scale precision landmark tool is also challenging to make. To solve these problems, we propose an automatic process to combine multiple composite targets, select keyframes, and estimate keyframe poses. The composite target consists of an aruco marker and a checkerboard pattern. First, an analytical method is applied to obtain initial values of all calibration parameters; prior knowledge of the calibration parameters is not required. Then, two optimization steps are used to refine the calibration parameters. Planar motion constraints of the camera are introduced in these optimizations. The proposed solution is automatic; manual selection of keyframes, initial values, and robot construction within a specific trajectory are not required. The competing accuracy and stability of the proposed method under different target placements and robot paths are tested experimentally. Positive effects on calibration accuracy and stability are obtained when (1) composite targets are adopted; (2) two optimization steps are used; (3) plane motion constraints are introduced; and (4) target numbers are increased.

ACS Style

Shusheng Bi; Dongsheng Yang; Yueri Cai. Automatic Calibration of Odometry and Robot Extrinsic Parameters Using Multi-Composite-Targets for a Differential-Drive Robot with a Camera. Sensors 2018, 18, 3097 .

AMA Style

Shusheng Bi, Dongsheng Yang, Yueri Cai. Automatic Calibration of Odometry and Robot Extrinsic Parameters Using Multi-Composite-Targets for a Differential-Drive Robot with a Camera. Sensors. 2018; 18 (9):3097.

Chicago/Turabian Style

Shusheng Bi; Dongsheng Yang; Yueri Cai. 2018. "Automatic Calibration of Odometry and Robot Extrinsic Parameters Using Multi-Composite-Targets for a Differential-Drive Robot with a Camera." Sensors 18, no. 9: 3097.