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International Conference on Information and Automation (ICIA)

作者： Yan Zhou Huiwen Guo Guoyuan Liang Xinyu Wu Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong

In this paper, we present an automatic method to remove shadows in light field images. Taking into account the internal structure of the light field data, depth map of the captured scene is extracted to calculate the surface normal. Using nonlocal matching by combining chromaticity, normal and spatial location information in an anisotropic window, the shadow confidence of each pixel is established. For effectively utilizing the prior knowledge, MRF (Markov random fields) is introduced to obtain the shadow label of each pixel iteratively. Once obtained the shadow labels of pixels, inpainting with an energy minimize framework is used to remove shadows. The experimental results on real data demonstrate good performance of this algorithm.

关键词： Image color analysis Cameras Computational modeling Computer vision Minimization Mathematical model Lighting

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Potential Guided Directional-RRT* for Accelerated Motion Planning in Cluttered Environments

Potential Guided Directional-RRT* for Accelerated Motion Pla...

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IEEE International Conference on Mechatronics and Automation

作者： Ahmed Hussain Qureshi Khawaja Fahad Iqbal Syeda Madiha Qamar Fahad Islam Yasar Ayaz Naveed Muhammad Robotics & Intelligent Systems Engineering (RISE) Lab Department of Robotics and Artificial Intelligence School of Mechanical & Manufacturing Engg (SMME) National University of Sciences & Technology (NUST) H-12 Campus Islamabad 44000 Pakistan.

ISBN: (纸本)9781467355599

Recently proposed Rapidly Exploring Random Tree Star (RRT*) algorithm which is an extension of Rapidly Exploring Random Tree (RRT) provides collision free asymptotically optimal path regardless of obstacle's geometry in a given environment. However, the drawback of this technique is a slow processing rate. This paper presents our proposed Potential Guided Directional-RRT* which addresses this problem and provides accelerated processing rate by incorporating Artificial Potential Fields Algorithm into RRT*. Artificial Potential Field algorithm directs the random samples toward the goal which leads to an increase in the speed of RRT*. We have presented simulation results of our technique and their comparison with results of RRT* under different environmental conditions to demonstrate apace execution rate of our novel idea.

关键词： RRT Artificial Potential Fields Sampling based motion planning

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When and How to Help: An Iterative Probabilistic Model for Learning Assistance by Demonstration

When and How to Help: An Iterative Probabilistic Model for L...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Harold Soh Yiannis Demiris Personal Robotics Lab Intelligent Systems and Networks Group Dept. of Electrical and Electronic Engineering Imperial College London SW7 2BT London United Kingdom

ISBN: (纸本)9781467363563

Crafting a proper assistance policy is a difficult endeavour but essential for the development of robotic assistants. Indeed, assistance is a complex issue that depends not only on the task-at-hand, but also on the state of the user, environment and competing objectives. As a way forward, this paper proposes learning the task of assistance through observation;an approach we term Learning Assistance by Demonstration (LAD). Our methodology is a subclass of Learning-by-Demonstration (LbD), yet directly addresses difficult issues associated with proper assistance such as when and how to appropriately assist. To learn assistive policies, we develop a probabilistic model that explicitly captures these elements and provide efficient, online, training methods. Experimental results on smart mobility assistance - using both simulation and a real-world smart wheelchair platform - demonstrate the effectiveness of our approach;the LAD model quickly learns when to assist (achieving an AUC score of 0.95 after only one demonstration) and improves with additional examples. Results show that this translates into better task-performance;our LAD-enabled smart wheelchair improved participant driving performance (measured in lap seconds) by 20.6s (a speedup of 137%), after a single teacher demonstration.

关键词： Iterative Probabilistic Model Learning Assistance by Demonstration LbD Probabilistic Model Wheelchair Iterative

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External localization system for mobile robotics

External localization system for mobile robotics

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International Conference on Advanced robotics (ICAR)

作者： Tomáš Krajník Matías Nitsche Jan Faigl Tom Duckett Marta Mejail Libor Přeučil University of Lincoln Lincoln Lincolnshire GB Lab. of Robotics and Emb. Systems Univ. of Buenos Aires Argentina Dpt. of Computer Science and Engineering FEE Czech Technical Univ. in Prague Lincoln Centre for Autonomous Systems Univ. of Lincoln United Kingdom Intelligent and Mobile Robotics Group FEE Czech Technical Univ. in Prague

We present a fast and precise vision-based software intended for multiple robot localization. The core component of the proposed localization system is an efficient method for black and white circular pattern detection. The method is robust to variable lighting conditions, achieves sub-pixel precision, and its computational complexity is independent of the processed image size. With off-the-shelf computational equipment and low-cost camera, its core algorithm is able to process hundreds of images per second while tracking hundreds of objects with millimeter precision. We propose a mathematical model of the method that allows to calculate its precision, area of coverage, and processing speed from the camera's intrinsic parameters and hardware's processing capacity. The correctness of the presented model and performance of the algorithm in real-world conditions are verified in several experiments. Apart from the method description, we also publish its source code; so, it can be used as an enabling technology for various mobile robotics problems.

关键词： Cameras Three-dimensional displays Robots Mathematical model Estimation Equations Detectors

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A manually-actuated MRI compatible robotic manipulator for image-guided interventions

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Physica Medica 2014年 30卷 e55-e56页

作者： Eftychios G. Christoforou Christoforos Keroglou Andrew Webb Nikolaos V. Tsekos Ioannis Seimenis KIOS Research Center for Intelligent Systems and Networks University of Cyprus Cyprus Department of Electrical and Computer Engineering University of Cyprus Cyprus C.J. Gorter Center for High Field MRI Leiden University Medical Center Leiden Netherlands Medical Robotics Laboratory University of Houston Houston TX USA Med. Physics Lab Medical School Democritus University of Thrace Alexandroupolis Greece

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Multi-robot Task Allocation for Search and Rescue Missions

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Journal of Physics: Conference Series 2014年第5期570卷

作者： Ahmed Hussein Mohamed Adel Mohamed Bakr Omar M Shehata Alaa Khamis Intelligent Systems Lab (LSI) Research Group Universidad Carlos III de Madrid (UC3M) Av. de la Universidad 30 28911 Madrid Spain Robotics and Autonomous Systems (RAS) Research Group German University in Cairo (GUC) 5th settlement – New Cairo 11432 Cairo Egypt Engineering Science Department Suez University Egypt and Vestec. Inc. 125 Northfield Drive West Waterloo N2L 6N8 Canada

Many researchers from academia and industry are attracted to investigate how to design and develop robust versatile multi-robot systems by solving a number of challenging and complex problems such as task allocation, group formation, self-organization and much more. In this study, the problem of multi-robot task allocation (MRTA) is tackled. MRTA is the problem of optimally allocating a set of tasks to a group of robots to optimize the overall system performance while being subjected to a set of constraints. A generic market-based approach is proposed in this paper to solve this problem. The efficacy of the proposed approach is quantitatively evaluated through simulation and real experimentation using heterogeneous Khepera-III mobile robots. The results from both simulation and experimentation indicate the high performance of the proposed algorithms and their applicability in search and rescue missions.

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Recent advances on the energy management of a Hybrid Electric vehicle

Recent advances on the energy management of a Hybrid Electri...

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2012 20th Mediterranean Conference on Control and Automation, MED 2012

作者： Efstathiou, D.S. Petrou, A.K. Spanoudakis, P. Tsourveloudis, N.C. Valavanis, K.P. Intelligent Systems and Robotics Lab Technical University of Crete Chania Greece Machine Tools Laboratory Technical University of Crete Chania Greece Department of Electrical and Computer Engineering University of Denver Denver CO 80208 United States

ISBN: (纸本)9781467325318

This paper presents new innovative subsystems of the ER11 prototype urban vehicle which is powered by hydrogen fuel cells and ultra-capacitors. The subsystems described here are: 1) the energy management system, which is responsible for the optimization of the fuel efficiency and the increased mileage of the vehicle, 2) the driver's monitoring and control panel and 3) the power transmission system, which offers the possibility of continuous change of gear. The powertrain of the test-bed vehicle consists of an electric motor, a fuel (H2) cell system, an ultra-capacitor bank and a DC/DC converter. Testing verified that the proposed energy management system is benefitted by the variable transmission of power leading to less fuel consumption. © 2012 IEEE.

关键词： Hybrid vehicles

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A multiple feature fusion model for image segmentation based on hierarchical visual pathway

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Advances in Information Sciences and Service Sciences 2012年第8期4卷 274-282页

作者： Hu, Dekun Li, Jianping Yang, Simon X. Gregori, Stefano School of Computer Science and Engineering University of Electronic Science and Technology of China China Advanced Robotics and Intelligent Systems Lab School of Engineering University of Guelph Canada

To segment an object from its background in an image for advanced vision processing, this paper presents a novel bio-inspired general framework for image segmentation in complex nature scenes, which is a hierarchical system that mimics the organization of layered early visual area in primate visual cortex. The proposed methodology consists of two typical stages: the first stage is a parallel modular structure including three segmenting operators based on color feature, form feature and texture feature, each of which solves the segmentation problem independently for the same input. Then, a fusion operation, multiple feature fusion segmentation (MFFS), integrates these three feature segmentations together through the backpropagation neuron network (BPNN) in the last stage, which simulates the operation of area following the lateral geniculate nucleus in primary visual cortex. The proposed approach is applied to several segmentation experiments of many single objects in clustering conditions, the result shows that the approach is capable of competing with state-of-the-art systems.

关键词： Neural networks

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An object recognition model with top-down prediction and context

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International Journal of Advancements in Computing Technology 2012年第12期4卷 283-290页

作者： Hu, Dekun Li, Jianping Yang, Simon X. University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu 611731 China University of Guelph School of Engineering Advanced Robotics and Intelligent Systems Lab Guelph ON Canada

Based on the trickle-up and trickle-down process in primate visual pathway, an ideal model for object recognition is researched. Firstly, the information of the low spatial frequency are extracted and passed to high visual cortex, the bank of the objects in memory is activated by this input, so the prediction of the possible candidate objects is pulled out. Then, the information of high spatial frequency, which keeps the invariability and selectivity of an object, is gained through the trickle-up process. With the top-down prediction, the context and the detailed information from trickle-up pathway, the object is recognized by Bayes inference. The performance of the proposed model is proved by several experiments.

关键词： Object recognition

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Recent advances on the energy management of a Hybrid Electric Vehicle

Recent advances on the energy management of a Hybrid Electri...

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Mediterranean Conference on Control & Automation

作者： D. S. Efstathiou A. K. Petrou P. Spanoudakis N. C. Tsourveloudis K. P. Valavanis Intelligent Systems and Robotics Lab Technical University of Crete Chania Greece Machine Tools Laboratory Technical University of Crete Chania Greece Department of Electrical and Computer Engineering University of Denver Denver CO 80208 USA

ISBN: (纸本)9781467325301

This paper presents new innovative subsystems of the ER11 prototype urban vehicle which is powered by hydrogen fuel cells and ultra-capacitors. The subsystems described here are: 1) the energy management system, which is responsible for the optimization of the fuel efficiency and the increased mileage of the vehicle, 2) the driver's monitoring and control panel and 3) the power transmission system, which offers the possibility of continuous change of gear. The powertrain of the test-bed vehicle consists of an electric motor, a fuel (Η2) cell system, an ultra-capacitor bank and a DC/DC converter. Testing verified that the proposed energy management system is benefitted by the variable transmission of power leading to less fuel consumption.

关键词： Recent advances energy management Hybrid Electric Vehicle

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