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IEEE/RSJ International Conference on intelligent robots and Systems

作者： P. Drews E. R. Nascimento M. F. M. Campos A. Elfes Department of Computer Science of the Universidade Federal de Minas Gerais - UFMG Belo Horizonte Brazil Centro de Ciências Computacionais - C3 Univ. Federal do Rio Grande - FURG Rio Grande Brazil Autonomous System Program - ASP CSIRO Pullenvale Australia

Underwater environments present a considerable challenge for computer vision, since water is a scattering medium with substantial light absorption characteristics which is made even more severe by turbidity. This poses significant problems for visual underwater navigation, object detection, tracking and recognition. Previous works tackle the problem by using unreliable priors or expensive and complex devices. This paper adopts a physical underwater light attenuation model which is used to enhance the quality of images and enable the applicability of traditional computer vision techniques images acquired from underwater scenes. The proposed method simultaneously estimates the attenuation parameter of the medium and the depth map of the scene to compute the image irradiance thus reducing the effect of the medium in the images. Our approach is based on a novel optical flow method, which is capable of dealing with scattering media, and a new technique that robustly estimates the medium parameters. Combined with structure-from-motion techniques, the depth map is estimated and a model-based restoration is performed. The method was tested both with simulated and real sequences of images. The experimental images were acquired with a camera mounted on a Remotely Operated Vehicle (ROV) navigating in a naturally lit, shallow seawater. The results show that the proposed technique allows for substantial restoration of the images, thereby improving the ability to identify and match features, which in turn is an essential step for other computer vision algorithms such as object detection and tracking, and autonomous navigation.

关键词： Image restoration Optical imaging Attenuation Cameras Lighting computer vision Estimation

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Autonomous flight and vision-based target tracking for a flapping-wing MAV

Autonomous flight and vision-based target tracking for a fla...

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IEEE/RSJ International Conference on intelligent robots and Systems

作者： Seungwan Ryu Ukjin Kwon H. Jin Kim Department of Mechanical and Aerospace Engineering Seoul National University Korea Department of Electrical and Computer Engineering Seoul National University Korea

ISBN: (纸本)9781509037636

In this paper, we design an autonomous flight controller for height regulation and bang-bang controller for directional control of a light-weight flapping-wing micro air vehicle (FWMAV) with limited payload. We also present autonomous vision-based target tracking for a FWMAV equipped with a low-cost and light-weight first person view (FPV) camera. We construct a ground station, integrated with control and vision algorithms, which performs the image processing and the computation of control inputs based on the acquired state variables from motion capture system. In addition, we employ a vision algorithm for a low-quality camera to detect a static target with the discussions on the techniques to improve the reliability of visual detection. Experimental results show satisfactory flight performance, achieving the height regulation and directional control, and autonomous vision-based target tracking.

关键词： Cameras Target tracking Vehicles Streaming media Actuators Data models Batteries

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Autonomous altitude estimation of a UAV using a single onboard camera

Autonomous altitude estimation of a UAV using a single onboa...

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2009 IEEE/RSJ International Conference on intelligent robots and Systems

作者： Anoop Cherian Jon Andersh Vassilios Morellas Nikolaos Papanikolopoulos Bernard Mettler Department of Computer Science University of Minnesota Minneapolis MN USA Department of AeroSpace Engineering University of Minnesota Minneapolis MN USA

Autonomous estimation of the altitude of an Unmanned Aerial Vehicle (UAV) is extremely important when dealing with flight maneuvers like landing, steady flight, etc. vision based techniques for solving this problem have been underutilized. In this paper, we propose a new algorithm to estimate the altitude of a UAV from top-down aerial images taken from a single on-board camera. We use a semi-supervised machine learning approach to solve the problem. The basic idea of our technique is to learn the mapping between the texture information contained in an image to a possible altitude value. We learn an over complete sparse basis set from a corpus of unlabeled images capturing the texture variations. This is followed by regression of this basis set against a training set of altitudes. Finally, a spatio-temporal Markov Random Field is modeled over the altitudes in test images, which is maximized over the posterior distribution using the MAP estimate by solving a quadratic optimization problem with L1 regularity constraints. The method is evaluated in a laboratory setting with a real helicopter and is found to provide promising results with sufficiently fast turnaround time.

关键词： Unmanned aerial vehicles Machine learning Helicopters intelligent robots USA Councils Robot vision systems Smart cameras computer science Machine learning algorithms Markov random fields

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Deep Learning-Based Visual Navigation algorithms for Mobile robots: A Comprehensive Study

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Journal of Computing and Information Technology 2022年第4期30卷 257-273页

作者： Yu, Wei Tian, Xinzhi Xi'an Siyuan University Shaanxi Xi'an China

This research addresses the challenges faced by mobile robots in efficiently navigating complex environments. A novel approach is proposed, leveraging deep learning techniques, and introducing the Neo model. The method combines Split Attention with the ResNeSt50 network to enhance the recognition accuracy of key features in the observed images. Furthermore, improvements have been made in the loss calculation method to improve navigation accuracy across different scenarios. Evaluations conducted on AI2THOR and active vision datasets demonstrate that the improved model achieves higher average navigation accuracy (92.3%) in scene 4 compared to other methods. The success rate of navigation reached 36.8%, accompanied by a 50% reduction in ballistic length. Additionally, compared to HAUSR and LSTM-Nav, this technology significantly reduced collision rates to 0.01 and reduced time consumption by over 8 seconds. The research methodology addresses navigation model accuracy, speed, and generalization issues, thus making significant advancements for intelligent autonomous robots. ACM CCS (2012) Classification: Computing methodologies → Machine learning → Machine learning algorithms Artificial intelligence → computer vision → vision for robotics. © 2022, University of Zagreb Faculty of Electrical Engineering and Computing. All rights reserved.

关键词： Navigation

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Scenario-based simulation of intelligent driving functions using neural networks

Scenario-based simulation of intelligent driving functions u...

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International Conference on Computing, Communication and Networking Technologies

作者： Parampreet Kaur Rajeev Sobti School of Computer Science Engineering Lovely Professional University Jalandhar India

The modern technological era is witnessing a significant advancement in AI related fields such as machine learning, mobile robots and autonomous vehicles. The success of such systems is immensely dependent on computer vision algorithms. The entirely software enabled intelligent vehicles will soon be hitting the roads in the coming decade. Such self-controlled mobile robots may still be vulnerable to accidents or crashes. Therefore, the industry requires some state of the art techniques to substantiate the safety and protection of its passengers as well as other road users. Simulation based testing methods have been in use from a long time, but the newer smart vehicle innovations require better versions of simulation techniques. We thus provide an improved mechanism for simulation testing to validate safe navigation of cars in variety of traffic scenarios. Neural network approach integrated with agent based modelling is described in this paper.

关键词： Agent based modelling intelligent driving SAE autonomy levels Simulation ADAS

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Towards vision-Based Impedance Control for the Contact Inspection of Unknown Generically-Shaped Surfaces with a Fully-Actuated UAV

Towards Vision-Based Impedance Control for the Contact Inspe...

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2020 IEEE/RSJ International Conference on intelligent robots and Systems (IROS)

作者： Ramy Rashad Davide Bicego Ran Jiao Santiago Sanchez-Escalonilla Stefano Stramigioli Robotics and Mechatronics group University of Twente Enschede The Netherlands School of Mechanical Engineering and Automation Beihang University Beijing China Robotics and Mechatronics group University of Twente and ITMO University Saint Petersburg Russia

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

The integration of computer vision techniques for the accomplishment of autonomous interaction tasks represents a challenging research direction in the context of aerial robotics. In this paper, we consider the problem of contact-based inspection of a textured target of unknown geometry and pose. Exploiting state of the art techniques in computer graphics, tuned and improved for the task at hand, we designed a framework for the projection of a desired trajectory for the robot end-effector on a generically-shaped surface to be inspected. Combining these results with previous work on energy-based interaction control, we are laying the basis of what we call vision-based impedance control paradigm. To demonstrate the feasibility and the effectiveness of our methodology, we present the results of both realistic ROS/Gazebo simulations and preliminary experiments with a fully-actuated hexarotor interacting with heterogeneous curved surfaces whose geometric description is not available a priori, provided that enough visual features on the target are naturally or artificially available to allow the integration of localization and mapping algorithms.

关键词： Surface impedance Inspection End effectors Trajectory Surface texture Impedance Task analysis

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Designing and making the intelligence assistant robot and controlling it by the fuzzy procedure

Designing and making the intelligence assistant robot and co...

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International Conference on Electronics, computer and Computation (ICECCO)

作者： Iman Zabbah Shima Foolad Bahram Chaharaqran Reza Mazlooman Department of computer Islamic Azad University Iran Department of computer Semnan University Semnan Iran Department of computer Maragheh Sanati University Maragheh Iran National Iranian Oil Products Distribution Company Iran

Mobile robots are those with the capability of moving in an environment. The controller of these robots needs to have the ability to do intelligent behaviours in an uncertain environment. Today fuzzy control of mobile robots in non-structured environments is increasing. Many represented algorithms for mobile robot navigation don't manifest appropriate performance in dynamic environments. This article aims at designing and making an intelligence robot. This robot is able to detect a specified target and track it. Velocity and steering of this robot is controlled by the fuzzy logic. Robot velocity is adjusted according to its distance from the target. This article is expressed the features of this mobile robot including different mechanical and electronic infrastructures, fuzzy navigation and vision controller. Navigation system of this robot makes its fuzzy decisions only based on the machine vision techniques and unlike many robots, it doesn't depend on sensor. It is concluded that robot with fuzzy navigation have 60% time saving than the non-fuzzy. The results obtained indicate its appropriate performance in order to navigate a target-oriented mobile robot in an undetermined and dynamic environment.

关键词： Mobile robots Robot kinematics Robot sensing systems Navigation Wheels DC motors

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Auditory and visual integration based localization and tracking of humans in daily-life environments

Auditory and visual integration based localization and track...

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2007 IEEE/RSJ International Conference on intelligent robots and Systems

作者： Hyun-Don Kim Kazunori Komatani Tetsuya Ogata Hiroshi G. Okuno Speech Media Processing Group Kyoto University Kyoto Japan

The purpose of this research is to develop techniques that enable robots to choose and track a desired person for interaction in daily-life environments. Therefore, localizing multiple moving sounds and human faces is necessary so that robots can locate a desired person. For sound source localization, we used a cross-power spectrum phase analysis (CSP) method and showed that CSP can localize sound sources only using two microphones and does not need impulse response data. An expectation-maximization (EM) algorithm was shown to enable a robot to cope with multiple moving sound sources. For face localization, we developed a method that can reliably detect several faces using the skin color classification obtained by using the EM algorithm. To deal with a change in color state according to illumination condition and various skin colors, the robot can obtain new skin color features of faces detected by OpenCV, an open vision library, for detecting human faces. Finally, we developed a probability based method to integrate auditory and visual information and to produce a reliable tracking path in real time. Furthermore, the developed system chose and tracked people while dealing with various background noises that are considered loud, even in the daily-life environments.

关键词： Humans Face detection Skin Change detection algorithms Microphones Lighting Robot vision systems computer vision Libraries Background noise

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Situation-oriented behavior-based stereo vision to gain robustness and adaptation in manipulator control

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3837卷 90-97页

作者： Nguyen, Minh-Chinh

ISBN: (纸本)0819434302

An new concept for visually guided manipulator control is introduced. It eliminates the need for a calibration of the manipulator as well as of the vision system and comprises an automatic adaptation to changing parameters. A key point of the concept is the achievement of a complex and elaborate desired goal by activating an appropriate sequence of rather simple elementary behaviors. Contrary to conventional stereo vision methods it uses an calibration-free camera system and allows a direct transition from image coordinates to motion control commands of a robot. By this approach, the abstract coordinate transformations have been avoided, instead, image data are used directly to control the behavior of the robot, or the interactions of the robot with physical objects. Thus, it makes knowledge of many hard-to-measure optical and mechanical system unnecessary;moreover, it lends itself to the realization of learning and adaptive robots. The concept has been successfully realized and tested in real-word experiments with an visually guided calibration-free 5 degree of freedom (DOF) manipulator involving the grasping of various objects with nearly any shape in arbitrary position (standing, lying, sloping) in the robot' 3-D work space.

关键词： computer vision

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An Adaptive Focal Connectivity Algorithm for Multifocus Fusion

An Adaptive Focal Connectivity Algorithm for Multifocus Fusi...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Harishwaran Hariharan Andreas Koschan Mongi Abidi Imaging Robotics and Intelligent Systems Laboratory University of Tennessee Knoxville TN USA

Multifocus fusion is the process of fusing focal information from a set of input images into one all-in-focus image. Here, a versatile multifocus fusion algorithm is presented for application-independent fusion. A focally connected region is a region or a set of regions in an input image that falls under the depth of field of the imaging system. Such regions are segmented adaptively under the predicate of focal connectivity and fused by partition synthesis. The fused image has information from all focal planes, while maintaining the visual verisimilitude of the scene. In order to validate the fusion performance of our method, we have compared our results with those of tiling and multiscale fusion techniques. In addition to performing a seamless fusion of the focally connected regions, our method out performs the competing methods regarding overall sharpness in all our experiments. Several illustrative examples of multifocus fusion are shown and objective comparisons are provided.

关键词： Layout Image segmentation Focusing Lenses Inspection Microscopy intelligent robots Partitioning algorithms Geometry intelligent systems

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