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2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Vinicius Graciano Santos Luiz Chaimowicz Vision and Robotics Laboratory (VeRLab) Computer Science Department Federal University Minas Gerais Brazil

Safe and efficient navigation of robotic swarms is an important research problem. One of the main challenges in this area is to avoid congestion, which usually happens when large groups of robots share the same environment. In this paper, we propose the use of hierarchical abstractions in conjunction with simple traffic control rules based on virtual forces to avoid congestion in swarm navigation. We perform simulated and real experiments in order to study the feasibility and effectiveness of the proposed algorithm. Results show that our approach allows the swarm to navigate without congestions in a smooth and coherent fashion, being suitable for large groups of robots.

关键词： Robot kinematics Robot sensing systems Collision avoidance Navigation Force Aerospace electronics

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A televiewing system for multiple simultaneous customized perspectives and resolutions

A televiewing system for multiple simultaneous customized pe...

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International Conference on Intelligent Transportation

作者： B. Hall Kohsia Huang M. Trivedi Computer Vision and Robotics Research Laboratory CVRR University of California La Jolla CA USA

Recent innovations in real-time machine vision, distributed computing, software architectures and high-speed communication are expanding the available technology for intelligent system development. These technologies allow the realization of intelligent systems that provide the capabilities for a user to experience events from remote locations in an interactive way. In this paper, we describe research aimed at the realization of a powerful televiewing system applied to the traffic incident detection and monitoring needs of today's highways. Sensor clusters utilizing both rectilinear and omni-directional cameras provide an interactive, real-time, multi-resolution televiewing interface to emergency response crews. Ultimately, this system will have a direct impact on reducing incident-related highway congestion by improving the quality of information to which emergency personnel have access.

关键词： Intelligent systems Machine intelligence Intelligent sensors Road transportation Technological innovation Real time systems Machine vision Distributed computing Software architecture Remote monitoring

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Are You With Me? Determining the Association of Individuals and the Collective Social Space

Are You With Me? Determining the Association of Individuals ...

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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Alan D. G. Silva Douglas G. Macharet Computer Vision and Robotics Laboratory (VeRLab) Universidade Federal de Minas Gerais MG Brazil

The increasing use of autonomous mobile robots in different parts of society, and not restricted only to industrial environments, makes it important to propose techniques that will allow them to behave in the most socially acceptable way as possible. In most real-world scenarios, individuals in the environment are interacting with each other and are arranged into groups. Therefore, it is paramount the proposition of techniques to efficiently and correctly identify and represent such groups. This information can be useful in different tasks such as approaching and initiating an interaction, escorting, and the navigation itself. In this work, we propose a novel graph-based approach to evaluate the possible association of individuals in the environment based on their position and body orientation. Next, based on this association, we propose a representation of the combined social space of individuals in the same group. The methodology was evaluated using synthetic and real-world datasets, showing that it achieves results comparable to or better than the state-of-the-art.

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Camera exposure control for robust robot vision with noise-aware image quality assessment

arXiv

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arXiv 2019年

作者： Shin, Ukcheol Park, Jinsun Shim, Gyumin Rameau, Francois Kweon, In So Robotics and Computer Vision Laboratory School of Electrical Engineering KAIST Daejeon34141 Korea Republic of

In this paper, we propose a noise-aware exposure control algorithm for robust robot vision. Our method aims to capture the best-exposed image which can boost the performance of various computer vision and robotics tasks. For this purpose, we carefully design an image quality metric which captures complementary quality attributes and ensures light-weight computation. Specifically, our metric consists of a combination of image gradient, entropy, and noise metrics. The synergy of these measures allows preserving sharp edge and rich texture in the image while maintaining a low noise level. Using this novel metric, we propose a real-time and fully automatic exposure and gain control technique based on the Nelder-Mead method. To illustrate the effectiveness of our technique, a large set of experimental results demonstrates higher qualitative and quantitative performances when compared with conventional approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： computer vision

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Deriving course 3D models of objects

Deriving course 3D models of objects

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Conference on computer vision and Pattern Recognition (CVPR)

作者： F.P. Ferrie M.D. Levine Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montreal QUE Canada

Much of the emphasis in computer vision research has been on recognizing objects. However, in order to perform tasks such as manipulating and avoiding collisions with objects, one needs to consider how to derive appropriate three-dimensional descriptions of objects from available sensor data. A description is given of a computational approach that has been successful in deriving renditions of shaded images in terms of volumetric primitives such as ellipsoids and cylinders.< >

关键词： Ellipsoids computer vision Shape Robot vision systems Laboratories Sensor phenomena and characterization Engine cylinders Robustness Eyes Collision avoidance

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Pose alignment of an eye-in-hand system using image morphing

Pose alignment of an eye-in-hand system using image morphing

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Singh R.M. Voyles D. Littau N.P. Papanikolopoulos Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science and Engineering University of Minnesota Minneapolis MN USA Artificial Intelligence Robotics and Vision Laboratory Department of Computer Science and Engineering University of Minnesota Minneapolis MN USA

Positioning an eye-in-hand robotic system with respect to a static target is a challenging research problem since it involves recognition of the object and the desired pose at which alignment is to occur, planning a trajectory for the robot to attain this pose, and careful calibration of the system and the environment. In this paper we introduce a unified framework based on image morphing, to address the above problems and apply it to the task of translational and rotational alignment of an eye-in-hand system to planar objects or planar projections of 3D objects. In our method the desired manipulator pose for each object is defined and stored as a view of the object taken from this pose. The identity of an unknown object in the workspace is established by morphing its image to the views in the database, and using a quantification of the morph as a dissimilarity measure. The synthetic images generated during the morph are used guide an eye-in-hand system to the desired pose. The framework can accommodate partially occluded or deformable targets and smooth trajectories can be generated since an arbitrary number of intermediate images can be used.

关键词： Calibration Robot vision systems Error correction Trajectory Artificial intelligence Intelligent robots Laboratories computer science Target recognition Image databases

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Hand modeling and tracking from voxel data: An integrated framework with automatic initialization

Hand modeling and tracking from voxel data: An integrated fr...

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International Conference on Pattern Recognition

作者： Cuong Tran Mohan M. Trivedi Computer Vision and Robotics Research Laboratory (CVRR) University of California San Diego CA USA

ISBN: (纸本)9781424421749

We propose an integrated framework for automated hand model initialization and tracking using voxel data. Starting with an initial specific hand pose, the Laplacian Eigenspace (LE) based segmentation method is applied to segment hand voxel into different parts. This segmentation result is then used to extend the kinematically constrained gaussian mixture model (KC-GMM) method for articulated body pose inference with an automated hand model initialization. Our experiment with both synthesized hand voxel and real hand voxel captured from multi-perspective thermal cameras show that by combining the two methods, we have a more powerful system than using each one solitarily.

关键词： Power system modeling Cameras Torso Human computer interaction Image reconstruction Kinematics computer vision Robot vision systems robotics and automation Laboratories

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No Robot Left Behind: Coordination to Overcome Local Minima in Swarm Navigation

No Robot Left Behind: Coordination to Overcome Local Minima ...

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2008 IEEE International Conference on robotics and Automation (ICRA 2008), vol.5

作者： Leandro Soriano Marcolino Luiz Chaimowicz Vision and Robotics Laboratory (VeRLab) Computer Science Department Federal University of Minas Gerais Brazil

In this paper, we address navigation and coordination methods that allow swarms of robots to converge and spread along complex 2D shapes in environments containing unknown obstacles. Shapes are modeled using implicit functions and a gradient descent approach is used for controlling the swarm. To overcome local minima, that may appear in these scenarios, we use a coordination mechanism that reallocates some robots as "rescuers" and sends them to help other robots that may be trapped. Simulations and real experiments demonstrate the feasibility of the proposed approach.

关键词： Robot kinematics Navigation Shape control robotics and automation Robot sensing systems Convergence Robot vision systems Motion planning Deformable models USA Councils

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Head and gaze dynamics in visual attention and context learning

Head and gaze dynamics in visual attention and context learn...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Anup Doshi Mohan M. Trivedi Laboratory for Intelligent and Safe Automobiles Computer Vision and Robotics Research Laboratory University of California San Diego USA

Future intelligent environments and systems may need to interact with humans while simultaneously analyzing events and critical situations. Assistive living, advanced driver assistance systems, and intelligent command-and-control centers are just a few of these cases where human interactions play a critical role in situation analysis. In particular, the behavior or body language of the human subject may be a strong indicator of the context of the situation. In this paper we demonstrate how the interaction of a human observer's head pose and eye gaze behaviors can provide significant insight into the context of the event. Such semantic data derived from human behaviors can be used to help interpret and recognize an ongoing event. We present examples from driving and intelligent meeting rooms to support these conclusions, and demonstrate how to use these techniques to improve contextual learning.

关键词： Humans Intelligent systems Intelligent robots Layout Monitoring Air traffic control Vehicle dynamics Cameras Laboratories Intelligent vehicles

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Leader tracking for a walking logistics robot

Leader tracking for a walking logistics robot

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： M. Perdoch D. M. Bradley J. K. Chang H. Herman P. Rander A. Stentz National Robotics Engineering Center Carnegie Mellon University ETH Zurich Computer Vision Laboratory

A key challenge of developing robots that work closely with people is creating a user interface that allows a user to communicate complex instructions to a robot quickly and easily. We consider a walking logistics support robot, which is designed to carry heavy loads to locations that are too difficult to reach with a wheeled or tracked vehicle. In this application the robot is carrying equipment and supplies for a group of pedestrians, and the primary task for the user interface is to keep the robot traveling with the overall group in the right formation. This paper presents a marker tracking system that uses near infrared cameras, retro-reflective markers, and LIDAR to allow a particular user to designate himself as the robot's leader, and guide the robot along a desired path. We provide an extensive quantitative evaluation to show that the proposed system is able to detect and track a leader through unconstrained and cluttered off-road environments under a wide variety of illumination and motion conditions.

关键词： Strips Detectors Laser radar Radar tracking Cameras Legged locomotion

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