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International Conference on intelligent Systems Design and Applications (ISDA)

作者： Ali Zia Tauseef Gulrez Tayyab Chaudhry Department of Computer Science Intelligent Machines & Robotics Research Group COMSATS Institute of Information Technology Lahore Pakistan

This paper addresses the problem of moving obstacle detection for autonomous mobile robots in unknown urban environments through the fusion of (vehicle-mounted) forward looking laser and vision sensors. In this approach we reparameterize the 2D gaussian distribution of the laser free-configuration eigenspaces by vision saliency gaussian kernel function. The approach uses bi-sensor paradigm to achieve greater effective mapping of the environment and improved accuracy in obstacle position estimation. Where the laser lower dimensional manifolds provide an eigenvector which corresponds to the free configuration space of the high order geometric representation of the environment and vision based edge detection followed by the saliency mapping provides the road detection and existance of dynamic obstacles on the road. We have shown that while the vectorial combination of eigenvectors at discrete time scan-frames of laser data manifest a trajectory, and once followed and fused with the vision sensor data, enables mobile robot to build an efficient and accurate online environment map free of obstacles. We demonstrated this process using real-time NAVLAB CMU (Autonomous Jeep's) data-set which is a good representation of autonomous mobile robot's navigation in an urban environment.

关键词： Robot sensing systems Laser modes Collision avoidance Mobile robots Gaussian distribution

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Underwater multi-robot convoying using visual tracking by detection

arXiv

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arXiv 2017年

作者： Shkurti, Florian Chang, Wei-Di Henderson, Peter Islam, Md Jahidul Higuera, Juan Camilo Gamboa Li, Jimmy Manderson, Travis Xu, Anqi Dudek, Gregory Sattar, Junaed Centre for Intelligent Machines School of Computer Science McGill University Interactive Robotics and Vision Laboratory Department of Computer Science and Engineering University of Minnesota- Twin Cities Element AI

We present a robust multi-robot convoying approach that relies on visual detection of the leading agent, thus enabling target following in unstructured 3-D environments. Our method is based on the idea of tracking-by-detection, which interleaves efficient model-based object detection with temporal filtering of image-based bounding box estimation. This approach has the important advantage of mitigating tracking drift (i.e. drifting away from the target object), which is a common symptom of model-free trackers and is detrimental to sustained convoying in practice. To illustrate our solution, we collected extensive footage of an underwater robot in ocean settings, and hand-annotated its location in each frame. Based on this dataset, we present an empirical comparison of multiple tracker variants, including the use of several convolutional neural networks, both with and without recurrent connections, as well as frequency-based model-free trackers. We also demonstrate the practicality of this tracking-by-detection strategy in real-world scenarios by successfully controlling a legged underwater robot in five degrees of freedom to follow another robot’s independent motion. Copyright © 2017, The Authors. All rights reserved.

关键词： Multipurpose robots

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Multi-robot forest coverage for unweighted terrain

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AIP Conference Proceedings 2013年第1期1558卷 2083-2086页

作者： Vladimir Popov Ural Federal University Department of Intelligent Systems and Robotics Mathematics and Computer Science Institute Lenin st. 51 620083 Ekaterinburg Russia

Different planning problems for mobile robots are of considerable interest for many years. Frequently, such problems require to solve different hard computational problems. Multi-robot forest coverage is one of such computational problems. In this paper, we consider an efficient approach to solve the problem of multi-robot forest coverage for unweighted terrain. In particular, we consider an explicit reduction from the decision version of the problem of multi-robot forest coverage for unweighted terrain to the satisfiability problem. For different satisfiability algorithms, the results of computational experiments are presented.

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SIFT texture description for understanding breast ultrasound images

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12th International Workshop on Breast Imaging, IWDM 2014

作者： Massich, Joan Meriaudeau, Fabrice Sentís, Melcior Ganau, Sergi Pérez, Elsa Puig, Domenec Martí, Robert Oliver, Arnau Martí, Joan Computer Vision and Robotics Group University of Girona Spain Laboratoire Le2i-UMR CNRS University of Burgundy Le Creusot France Department of Breast and Gynecological Radiology UDIAT-Diagnostic Center Parc Taulí Corporation Sabadell Spain Department of Radiology Hospital Josep Trueta of Girona Spain Department of Computer Engineering and Mathematics University Rovira I Virgili Tarragona Spain

ISBN: (纸本)9783319078861

Texture is a powerful cue for describing structures that show a high degree of similarity in their image intensity patterns. This paper describes the use of Self-Invariant Feature Transform (SIFT), both as low-level and high-level descriptors, applied to differentiate the tissues present in breast US images. For the low-level texture descriptors case, SIFT descriptors are extracted from a regular grid. The high-level texture descriptor is build as a Bag-of-Features (BoF) of SIFT descriptors. Experimental results are provided showing the validity of the proposed approach for describing the tissues in breast US images. © 2014 Springer International Publishing.

关键词： Ultrasonics

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Inverse Kinematics of Robotic Manipulators Using a New Learning-by-Example Method

Inverse Kinematics of Robotic Manipulators Using a New Learn...

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

作者： Jacket Demby’s Ramy Farag Guilherme N. DeSouza Department of Electrical Engineering and Computer Science (EECS) Vision-Guided and Intelligent Robotics (ViGIR) Laboratory University of Missouri-Columbia Columbia Missouri

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Inverse Kinematics (IK) is one of the most fundamental challenges in robotics. It refers to the process of determining the joint configurations required to achieve the desired position and orientation (pose) of a robot end-effector. Although numerous Data-Driven (DD) IK solvers have demonstrated encouraging results, they have not achieved the same accuracy when compared to other IK methods for complex robot configurations (e.g., numerical methods for higher Degrees of Freedom (DoF)). In this work, we propose a new Learning-by-Example method, and show that such a scheme considerably improves the IK learning results when compared to other DD learners. In our approach, the network input incorporates an example of joint-pose pair along with the query pose to predict the desired robot joint configuration. We show that the example joint-pose pair does not need to be too close to the query – i.e. example and query can be as far as 20 degrees apart in the joint configuration space. Furthermore, we investigate the utilization of residual and dense skip connections in Multilayer Perceptron for DDIK solvers and employ the resulting networks for two redundant robotic manipulators: a 7-DoF-7R commensurate robot and a 7DoF-2RP4R incommensurate robot. Our experimental results show that the resulting DDIK solver can reliably predict IK solutions with accuracy better than 1mm in position and 1deg in orientation.

关键词： Hands Accuracy Kinematics Network architecture Multilayer perceptrons Numerical models Reliability Collision avoidance Robots intelligent robots

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Cognitive Approach to Hierarchical Task Selection for Human-Robot Interaction in Dynamic Environments

Cognitive Approach to Hierarchical Task Selection for Human-...

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

作者： Syed Tanweer Shah Bukhari Bashira Akter Anima David Feil-Seifer Wajahat Mahmood Qazi Cognitive Robotics Group Faculty of IT and CS University of Central Punjab Lahore Pakistan Department of Computer Science Intelligent Machines & Robotics Group COMSATS University Islamabad Pakistan Department of Computer Science & Engineering Socially Assistive Robotics Group University of Nevada Reno Reno NV USA

In an efficient and flexible human-robot collaborative work environment, a robot team member must be able to recognize both explicit requests and implied actions from human users. Identifying “what to do” in such cases requires an agent to have the ability to construct associations between objects, their actions, and the effect of actions on the environment. In this regard, semantic memory is being introduced to understand the explicit cues and their relationships with available objects and required skills to make “tea” and “sandwich”. We have extended our previous hierarchical robot control architecture to add the capability to execute the most appropriate task based on both feedback from the user and the environmental context. To validate this system, two types of skills were implemented in the hierarchical task tree: 1) Tea making skills and 2) Sandwich making skills. During the conversation between the robot and the human, the robot was able to determine the hidden context using ontology and began to act accordingly. For instance, if the person says “I am thirsty” or “It is cold outside” the robot will start to perform the tea-making skill. In contrast, if the person says, “I am hungry” or “I need something to eat”, the robot will make the sandwich. A humanoid robot Baxter was used for this experiment. We tested three scenarios with objects at different positions on the table for each skill. We observed that in all cases, the robot used only objects that were relevant to the skill.

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Development of a mammographic analysis system using computer vision techniques 2

引用

2nd International Symposium on Medical Data Analysis, ISMDA 2001

作者： Martí, J. Planiol, P. Freixenet, J. Español, J. Golobardes, E. University of Girona Computer Vision and Robotics Group – IIiA Campus de Montilivi Girona17071 Spain University Hospital of Girona "Dr. Josep Trueta" Department of Oncology Avda. de Fraņca s/n Girona17071 Spain Universitat Ramon Llull Computer Science Department Passeig Bonanova 8 Barcelona08022 Spain

ISBN: (纸本)3540427341

This work presents an application intended to work as a second reader in Radiology Services for digital mammograms, which makes use of several computer vision algorithms. Although the presented prototype basically focuses on the detection and the characterization of microcalcifications, the system has the capability to grow up by adding new abnormalities (e.g. masses) or new classification patterns. Experimental results of the system’s performance have been obtained through digital mammograms of the Regional Health Area of Girona. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Mammography

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IEEE Transactions on Haptics: Editorial

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IEEE Transactions on Haptics 2008年第1期1卷 2-8页

作者： Edward Colgate, J. Lederman, Susan Prattichizzo, Domenico Barbagli, Federico Basdogan, Cagatay Buss, Martin Ernst, Marc Frisoli, Antonio Gillespie, Brent Grant, Danny Harders, Matthias Hayward, Vincent Jones, Lynette Kajimoto, Hiroyuki Kappers, Astrid Kheddar, Abderrahmane Lin, Ming C. MacLean, Karon Miller, Brian Noma, Haruo Okamura, Allison M. O'Malley, Mareia Ryu, Jeha Tan, Hong Z. Yokokohji, Yasuyoshi Department of Psychology School of Computing Queen's University Canada IEEE Robotics and Automation Society Tübingen Germany Stanford University's Computer Science Department Tübingen Germany Institute of Automatic Control Engineering Technische Universität München Germany Independent Research Group Multisensory Perception and Action Max Planck Institute for Biological Cybernetics Tübingen Germany Department of Applied Mechanics SSSA Japan Research Division Virtual Reality and Telerobotic Systems PERCRO Laboratory Japan Department of Mechanical Engineering Japan Department of Robotics McGill University Canada Computer Vision Lab ETH Zurich Japan Virtual Reality in Medicine Group Japan IEEE CS/RAS Technical Committee on Haptics Japan Department of Electrical and Computer Engineering McGill University Canada Department of Mechanical Engineering MIT Japan University of Electro-Communications Japan Department of Physics and Astronomy Utrecht University Netherlands University of Evry France Chapel Hill United States Department of Computer Science University of British Columbia Canada ATR Knowledge Science Lab United Kingdom Department of Mechanical Engineering Denmark Johns Hopkins University United States Laboratory for Computational Sensing and Robotics United Kingdom Engineering Research Center for Computer-Integrated Surgical Systems and Technology United States Mechanical Engineering and Materials Science Department Rice University United States Korea Republic of Department of Electrical and Computer Engineering Mechanical Engineering and Psychological Sciences Purdue University United States Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Japan

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Map building with ultrasonic sensors of indoor environments using neural networks

Map building with ultrasonic sensors of indoor environments ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： F.J. Toledo J.D. Luis L.M. Tomas M.A. Zamora H. Martinez Department of Computer Science and Elect University de Murcia Murcia Spain Vision and Robotics Group University of Murcia Murcia Spain

Map building and position estimation are basic tasks in mobile robot navigation with path planning. A method to generate a global map of the vehicle work environment using ultrasonic sensors is developed in this paper. Depending on the physical properties of the walls that form the room where the robot is navigating, sonar sensors show different behaviours. A neural network is utilized to interpret the range readings of ultrasonic sensors in the different environments. A local map composed of squared cells is formed through the neural network that gives the occupancy probabilities for each cell. Finally, a global map is built achieving integration of different views of the environment using Bayes' rule. Results of the method implementation in the construction in a specular environment as well as in rough wall environments are shown in this paper.

关键词： Indoor environments Neural networks Robot sensing systems Reflection Mobile robots Sonar navigation Path planning Robustness Testing Sonar measurements

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***: Transforming Colour into Melody and Implementing the Result in a Colour Sensor Device

***: Transforming Colour into Melody and Implementing the Re...

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International Conference on Visualisation, VIS

作者： Jessica Rossi Francisco Jose Perales Javier Varona Miquel Roca Computer Graphics Vision and Artificial Intelligence Group Mathematics and Computers Science Department University of Balearic Islands Spain

This paper represents a system which explores the reality of colour in relation to sound and dedicated firstly to blind people, the challenges they live with, their psychology and their emotions. Itpsilas an exploration of the infinite range of colours that they have either never been able to see or that they have lost the possibility to see. The system developed is based on the concept of synesthesia: a dasialiaisonpsila between colour and sound, colour that becomes sound. This paper synthesizes a wider range of study regarding people with diverse psychological and movement conditions. It represents a new method of expression and of self development through music therapy and game, dedicated mainly to children aged between 5 and 13. Finally we conclude with a portable prototype device that has been validated and patented. It is capable of detecting colour and transforming it into sound: a colour sensor identifies colours and transforms this data into musical notes. The prototype is totally adaptable to the requirements of the end user meaning that the user can choose the best combination between colour and sound in order to improve their communication with the environment. We are now developing a mathematical theoretical background in order to formalize the correspondence between colour and musical space.

关键词： Psychology Acoustic sensors Prototypes Cultural differences Auditory system vision defects Visualization intelligent sensors Sensor systems computer graphics

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