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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

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Comparison Between MATLAB Bundle Adjustment Function and Parallax Bundle Adjustment

Comparison Between MATLAB Bundle Adjustment Function and Par...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Hongkyoon Byun Liang Zhao Jonghyuk Kim Shoudong Huang Faculty of Engineering and Information Technology Robotics Institute University of Technology Sydney Ultimo NSW Australia

ISBN: (纸本)9781665476881

Bundle Adjustment (BA) takes a crucial part in Structure from Motion (SfM) which refines a visual reconstruction by optimizing the camera poses and feature positions. the performance of BA can differ depending on the parametrization methods. this paper evaluates two bundle adjustment techniques using standard BA function from MATLAB and Parallax BA. the two BA techniques are compared using data from the “Starry Night” and “MALAGA Parking-6L” with different initial inputs. the accuracy and convergence properties of the two BA methods have been evaluated. the effect of the different parameterization techniques and initial information was also analyzed. In most cases, the results of Parallax BA show better accuracy with lower final reprojection error and are less sensitive to the initialization values. It is evaluated that the parallax angle avoids the singularity issue commonly found in Standard BA, which shows that Parallax BA outperforms Standard BA. Furthermore, visual-inertial SLAM (VI-SLAM), based on Parallax BA, has been presented. It is much more reliable than a pure-vision system, showing further improved performance in terms of robustness and accuracy, even with less feature observation. the open-source code can be found in: https://***/uts-hb/***

关键词： Bundle adjustment Visualization Simultaneous localization and mapping Structure from motion Cameras Robustness Standards

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the long-acting walking control of a cockroach bio-bot for vision-aided pipeline navigation

The long-acting walking control of a cockroach bio-bot for v...

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Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Songsong Ma Shen Liu Songlin Yang Yuansheng Chen Yao Li Bing Li State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin P.R. China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Harbin Institute of Technology Shenzhen P.R. China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen P.R. China

Many small bionic crawling robots have been invented for search and rescue missions in narrow spaces. However, their locomotion capability is far from that of insects of the same size. Transforming a cockroach into a bio-bot has been a hot topic in the past decade. Herein, we modified this insect to perform surveillance work in dark confined environments. the synergistic electrical stimulation for turning control was proposed by alternating electrical stimulation of the cerci and antennae every 5 trials. the result showed that this method was able to control cockroaches turning steadily 117 times. An electronic backpack was designed, which was capable of transmitting images in real time, and a light emitting diode (LED) was installed on the backpack providing a light source for the camera. thus, a vision-aided navigation system was formed for dark confined environments, e.g. pipelines. With a host computer software, the operator controlled the bio-bot to pass through a completely dark and closed pipeline. the electronic backpack and the host computer were connected via transmission control protocol (TCP), which allows the operator to manipulate the bio-robot remotely. this technology can be applied in pipeline surveillance in the future.

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Robust Training of Object Detection with Sparse Annotations

Robust Training of Object Detection with Sparse Annotations

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international conference on control, automation, robotics and vision (ICARCV)

作者： Li Quan Xueyan Zhang Chunming Liu Xing Wang Yirong Ma Jin Shi Beijing Tellhow Intelligent Engineering Co. Ltd. Beijing China North China Electric Power University Beijing China

ISBN: (纸本)9781665476881

It is difficult to annotate all instances for object detection tasks in practice, especially facing the crowned scenes. the model performance could be impaired when training on sparsely annotated datasets, compared to fully annotated ones. To alleviate this problem, we propose a novel robust training framework for sparsely annotated object detection. We take the sparse annotations as a special case of noisy annotations, where the instances without annotations are regarded as background. First, we propose an Ensemble Prediction (EP) module from different temporal models to avoid the model fitting to the background (noisy labels). Further, an Ensemble Models Non-Maximum Suppression (EM-NMS) module is proposed based on the EP module to generate more robust bounding boxes. Finally, the Pseudo Labels Generating (PLG) module is used to produce pseudo labels for the possible missing-annotation instances. Extensive validation experiments are conducted on PASCAL VOC and MS COCO datasets with sparse annotations. the results show that our proposed robust training framework can further improve model performance when compared to related studies.

关键词： Training automation Annotations Fitting Object detection Predictive models Semisupervised learning

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What's on the Other Side? A Single-View 3D Scene Reconstruction

What's on the Other Side? A Single-View 3D Scene Reconstruct...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Rafał Staszak Bartłomiej Kulecki Witold Sempruch Dominik Belter Institute of Robotics and Machine Intelligence Poznan University of Technology Poznan Poland

ISBN: (纸本)9781665476881

Robots have limited perception capabilities when observing a new scene. When the objects on the scene are registered from a single perspective, only partial information about the shape of the objects is registered. Incomplete models of objects influence the performance of grasping methods. In this case, the robot should scan the scene from other perspectives to collect information about the objects or use methods that fill in unknown regions of the scene. the CNN-based method for objects reconstruction from a single view utilize 3D structures like point clouds or 3D grids. In this research, we revisit the problem of scene reconstruction and show that scene reconstruction can be formulated in the 2D image space. We propose a new representation of the scene reconstruction problem for a robot equipped with an RGB-D camera. then, we present a method that generates a depth image of the object from the pose of the camera that is on the other side of the scene. We show how to train a neural network to obtain accurate depth images of the objects and reconstruct a 3D model of the scene observed from a single viewpoint. Moreover, we show that the obtained model can be applied to improve the success rate of the grasping method.

关键词： Point cloud compression three-dimensional displays Shape Robot vision systems Neural networks Grasping Cameras

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An Unsupervised Learning Approach to Handle Movement Epenthesis in Continuous Sign Language Recognition

An Unsupervised Learning Approach to Handle Movement Epenthe...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Navneet Nayan Debashis Ghosh Pyari Mohan Pradhan Department of ECE Indian Institute of Technology Roorkee Haridwar India

ISBN: (纸本)9781665476881

In this paper, the problem of movement epenthesis in continuous sign language sentences is considered. Movement epenthesis caused due to unwanted but unavoidable hand movement in between two sign gestures in continuous signing has emerged as one of the most challenging problems in automatic sign language recognition. To handle this problem, a novel method based on unsupervised learning approach has been proposed in this paper to separate out video frames corresponding to meaningful sign gestures from meaningless movement epenthesis segments in a continuous signing gesture video clip. Our proposed method is based on K-means clustering of the norm values of the absolute difference between current frames and the reference frame to detect the movement epenthesis frame and then classify the frames of the video as movement epenthesis frames and sign frames. Exhaustive experimentation on the publicly available standard ChaLearn LAP ConGD gesture video dataset was carried out to test our algorithm. Experimental results demonstrate that the proposed method is good enough to detect and separate out the movement epenthesis frames in sentence level sign language videos. Our proposed approach performs the movement epenthesis detection task accurately in 91% of the videos of the ChaLearn LAP ConGD dataset.

关键词： automation Gesture recognition Assistive technologies Classification algorithms Task analysis Unsupervised learning Standards

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No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor 16

No-attachment head tracking method of robotic transcranial m...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Yu Chen Wang Xin Lu ZongJie Su HuanRan Harbin Inst Technol CO-518000 Shenzhen Peoples R China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177090

A vision-based head tracking method for robotic transcranial magnetic stimulation (TMS), requiring no attachments to patient, is proposed to track the movements of patient's head during treatment. First, a facial landmark detection method based on Constrained Local Neural Field (CLNF) algorithm is used. Second, a method of head location and pose estimation is presented and a filter for image restoration is used for a higher accuracy. Finally, calibration approaches are proposed based on the coordinates of the robot arm and camera and real-time motion tracking system. Experiment results indicate that the accuracy and real-time performance of this head tracking method satisfy the requirements of TMS treatment.

关键词： Head Magnetic heads Cameras Robot kinematics Calibration Faces Magnetic resonance imaging

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Two-Ts: Development of a Robotic Head to Reproduce Facial Emotions Using 3D Printing Technology

Two-Ts: Development of a Robotic Head to Reproduce Facial Em...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Tamires dos Santos Wagner Tanaka Botelho Edson Pinheiro Pimentel Flavio Shigeo Yamamoto Federal University of ABC Centre of Mathematics Computation and Cognition Brazil Startup NTU Software Technology

ISBN: (纸本)9781665476881

A robotic head has a key role in exchanging information to indicate its emotional state or communicate during an interaction. therefore, the main target of this paper is to present the open-source and low-cost robot head, known as Two-Ts, which is developed using 3D printing technology. Its main feature is to reproduce, even with mechanical limitations, the six basic and universal emotions created according to the Facial Action Coding System (FACS). Two steps are necessary for its development. In the first step, as the objective of the Two-Ts is to have characteristics closer to a human head, a Computer Tomography (CT) is performed to scan images of the bones of the skull and jaw of Tamires, author of this paper. In the second step, using the generated images, the structural/mechanical design of the Virtual Two-Ts is modeled and simulated in Autodesk Fusion 360. Before developing the Real Two-Ts, the electronic project is also defined, considering the vision, hearing, and speech systems. In the simulation and real experiment, the Virtual and Real Two-Ts perform basic movements, such as moving the eyes, eyebrows, head, among others. In addition, the emotions of happiness, fear, disgust, anger, surprise, and sadness are implemented, and the results are analyzed. For this, a system is developed to identify and compare the emotions generated on the face of Tamires with those of Virtual and Real Two-Ts.

关键词： automation Computed tomography Computational modeling Auditory system three-dimensional printing Bones Encoding

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Furuta pendulum real-time system with brushless DC motor and cascade hybrid control 16

Furuta pendulum real-time system with brushless DC motor and...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Cholodowicz, Ewelina Orlowski, Przemyslaw West Pomeranian Univ Technol Szczecin Fac Elect Engn Szczecin Poland

ISBN: (纸本)9781728177090

the inverted pendulum is one of the popular testbeds in the control theory education, owning to its complex characteristics (nonlinear, underactuated), along with its real-world applications, for example in transportation, walking of robots etc. this paper is dedicated to the problem of Furuta pendulum control. It describes a mathematical model of the Furuta pendulum, the linearization process and the results of the identification experiment. Two methods for the brushless DC motor control have been proposed. the last section is dedicated to the achievements of experimental research on control systems implementation. the main aim of this work is to present the achievements of the designed stand and to compare two different approaches of Furuta pendulum control with brushless DC motor. On the basis of the conducted research, it is stated that a magnetic encoder control allows a more effective and better tracking of the setpoint with respect to the modelling inaccuracy in comparison to the sinusoidal generator controller.

关键词： Brushless DC motors

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Smooth Adaptive Leader-Following Consensus control for Uncertain Fractional-Order Nonlinear Multi-Agent Systems with Time-Varying Reference 16

Smooth Adaptive Leader-Following Consensus Control for Uncer...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Li, Xinyao Wen, Changyun Li, Xiaolei Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

ISBN: (纸本)9781728177090

In this paper, the leader-following consensus control problem is studied for fractional-order nonlinear multi-agent systems in the presence of system uncertainties and unknown external disturbances. An adaptive distributed control scheme is proposed for each agent with a local controller that contains a filter and estimators for estimating the bounds of the fractional-order derivatives of desired trajectory. All the control signals resulted from the control scheme are smooth and they are still able to achieve asymptotic output consensus tracking while ensuring global boundedness of all the closed-loop signals. Simulation results are provided to illustrate the effectiveness of the proposed control protocol and verify the obtained results.

关键词： Multi agent systems

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Cooperative control Based on Distributed Attack Identification and Isolation 16

Cooperative Control Based on Distributed Attack Identificati...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Liu, Hailing Huang, Dalin Zhang, Ya Southeast Univ Sch Cyber Sci & Engn Nanjing Peoples R China Southeast Univ Sch Automat Nanjing Peoples R China Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing Peoples R China

ISBN: (纸本)9781728177090

this paper studies the secure consensus control of multi-agent systems where some agents are injected into malicious attacks and compromised. We focus on the distributed detection and identification of attacks on agents and the realization of consensus of agents against attacks. Firstly, we design monitors that can perform precise distributed attack detection. then, we propose a distributed attack identification algorithm by constructing distributed observers. After that, a cooperative controller is proposed which ensures the normal control of systems by means of isolating the agents which are attacked. Finally, we validate our results through simulation examples.

关键词： Multi agent systems

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