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Speed Daemon: Experience-based Mobile robot Speed Scheduling

Speed Daemon: Experience-based Mobile Robot Speed Scheduling

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11th canadian conference on computer and robot vision (CRV)

作者： Ostafew, Chris J. Schoellig, Angela P. Barfoot, Timothy D. Collier, Jack Univ Toronto Inst Aerosp Studies Toronto ON Canada Def Res & Dev Canada Suffield AB Canada

ISBN: (纸本)9781479943388

A time-optimal speed schedule results in a mobile robot driving along a planned path at or near the limits of the robot's capability. However, deriving models to predict the effect of increased speed can be very difficult. In this paper, we present a speed scheduler that uses previous experience, instead of complex models, to generate time-optimal speed schedules. the algorithm is designed for a vision-based, path-repeating mobile robot and uses experience to ensure reliable localization, low path-tracking errors, and realizable control inputs while maximizing the speed along the path. To our knowledge, this is the first speed scheduler to incorporate experience from previous path traversals in order to address system constraints. the proposed speed scheduler was tested in over 4 km of path traversals in outdoor terrain using a large Ackermann-steered robot travelling between 0.5 m/s and 2.0 m/s. the approach to speed scheduling is shown to generate fast speed schedules while remaining within the limits of the robot's capability.

关键词： Speed Scheduling Experience-based Mobile robotics

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Navigation Assistance for a BCI-controlled Humanoid robot 4

Navigation Assistance for a BCI-controlled Humanoid Robot

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4th IEEE Annual International conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

作者： Petit, Damien Gergondet, Pierre Cherubini, Andrea Meilland, Maxime Comport, Andrew I. Kheddar, Abderrahmane CNRS AIST Joint Robot Lab JRL CRT UMI3218 Tsukuba Ibaraki Japan CNRS UM2 LIRMM Interact Digital Human Grp UMR5506 Montpellier France Univ Nice Sophia Antipolis CNRS I3S Lab Nice France

ISBN: (纸本)9781479936694

We present an assisted navigation scheme designed to control a humanoid robot via a brain computer interface in order to let it interact with the environment and with humans. the interface is based on the well-known steady-state visually evoked potentials (SSVEP) and the stimuli are integrated into the live feedback from the robot embedded camera displayed on a Head Mounted Display (HMD). One user controlled the HRP-2 humanoid robot in an experiment designed to measure the performance of the new navigation scheme based on visual SLAM feedback. the new navigation scheme performance is tested in an experience where the user is asked to navigate to a certain location in order to perform a task. It results that without the navigation assistance it is much more difficult to reach the appropriate pose for performing the task. the detailed results of the experiments are reported in this paper, and we discuss the possible improvements of our novel scheme.

关键词： Cameras Collision avoidance Humanoid robots Manuals Navigation robot vision systems Humanoid robots navigation robot vision system Cameras Collision avoidance Brain-computer Interfaces Helmet mounted displays

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Design and implementation of machine vision for board game in lumen social robot system 4

Design and implementation of machine vision for board game i...

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2014 4th IEEE International conference on System Engineering and Technology, ICSET 2014

作者： Subekti, Petrus Fajar Setijadi, Ary Rohman, Arief Syaichu School of Electrical Engineering and Informatics Institut Teknologi Bandung Jalan Ganesha No. 10 Bandung40132 Indonesia

ISBN: (纸本)9781479971893

Machine vision on Humanoid robot Nao, is homology with eye. the success of machine vision is heavily determined by interpretation process to get information of environment and object. this information will be used for decision making of robot action. On this research, machine vision will be applied for tictac-toe board game. this research will become stepping stone for machine vision method for robotic control. On this design and implementation, image interpretation, along with data communication and geometrical analysis will be processed to estimate position accurately and precisely. Furthermore, information is extracted from an image that made robot to recognize and interact with board game pawns. Decision making application will process information to give decision about game action of Nao robot. the decision will be executed by robot's arm actuator. the system runs well during the testing when battling with human player. © 2014 IEEE.

关键词： Anthropomorphic robots

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Distributed sensor network for multi-robot surveillance

Distributed sensor network for multi-robot surveillance

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5th International conference on Ambient Systems, Networks and Technologies (ANT) / 4th International conference on Sustainable Energy Information Technology (SEIT)

作者： Pennisi, A. Previtali, F. Ficarola, F. Bloisi, D. D. Iocchi, L. Vitaletti, A. Univ Roma La Sapienza Dept Comp Control & Management Engn Rome Italy

Monitoring of populated indoor environments is crucial for the surveillance of public spaces like airports or embassies, where the behavior of people may be relevant in order to determine abnormal situations. In this paper, a surveillance system based on an integration of interactive and non-interactive heterogeneous sensors is described. As a difference with respect to traditional, pure vision-based systems, the proposed approach relies on Radio Frequency Identification (RFID) tags carried by people, multiple mobile robots (each one equipped with a laser range finder and an RFID reader), and fixed RGBD cameras. the main task of the system is to assess the presence and the position of people in the environment. this is obtained by suitably integrating data coming from heterogeneous sensors, including those mounted on board of mobile robots that are in charge of patrolling the environment. the robots also adapt their behavior according to the current situation, on the basis of a Prey-Predator scheme. Experimental results carried out both on real and on simulated data show the effectiveness of the approach. (C) 2014 Published by Elsevier B.V.

关键词： Mobile robots Wireless Sensor Networks Multi-robot Systems Multi-robot Surveillance

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Sign Language Fingerspelling Classification from Depth and Color Images using a Deep Belief Network

Sign Language Fingerspelling Classification from Depth and C...

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11th canadian conference on computer and robot vision (CRV)

作者： Rioux-Maldague, Lucas Giguere, Philippe Carleton Univ Sch Comp Sci Ottawa ON K1S 5B6 Canada Univ Laval Sch Comp Sci Quebec City PQ G1K 7P4 Canada

ISBN: (纸本)9781479943388

Automatic sign language recognition is an open problem that has received a lot of attention recently, not only because of its usefulness to signers, but also due to the numerous applications a sign classifier can have. In this article, we present a new feature extraction technique for hand pose recognition using depth and intensity images captured from a Microsoft Kinect(TM) sensor. We applied our technique to American Sign Language fingerspelling classification using a Deep Belief Network, for which our feature extraction technique is tailored. We evaluated our results on a multi-user data set with two scenarios: one with all known users and one with an unseen user. We achieved 99 % recall and precision on the first, and 77 % recall and 79 % precision on the second. Our method is also capable of real-time sign classification and is adaptive to any environment or lightning intensity.

关键词： Deep Learning Depth Features Hand Pose Recognition Fingerspelling

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A new method of image matching in a vision-based mobile robot system

A new method of image matching in a vision-based mobile robo...

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4th International conference on Materials Science and Information Technology, MSIT 2014

作者： Cao, Cheng-Zhi Gao, Wen-Zheng Li, Hui-Jun Center for Computer Fundamental Education Jilin University Changchun 130012 China Audi China Enterprise Management Co. Ltd Building B6 751D park Jiuxianqiao Road Beijing 100000 China

ISBN: (纸本)9783038351733

In a vision-based system for mobile robot/human localization in the environment, extracting feature from images and image matching are important for the final results. Although there are many algorithms for image matching, they are not fit for this system. A new method is designed to improve image matching effect. © (2014) Trans Tech Publications, Switzerland.

关键词： Image matching

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Towards Estimating Bias in Stereo Visual Odometry

Towards Estimating Bias in Stereo Visual Odometry

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11th canadian conference on computer and robot vision (CRV)

作者： Farboud-Sheshdeh, Sara Barfoot, Timothy D. Kwong, Raymond H. Univ Toronto Fac Elect & Comp Engn Toronto ON M5S 3G4 Canada Univ Toronto Inst Aerosp Studies N York ON M3H 5T6 Canada

ISBN: (纸本)9781479943388

Stereo visual odometry (VO) is a common technique for estimating a camera's motion;features are tracked across frames and the pose change is subsequently inferred. this position estimation method can play a particularly important role in environments in which the global positioning system (GPS) is not available (e. g., Mars rovers). Recently, some authors have noticed a bias in VO position estimates that grows with distance travelled;this can cause the resulting position estimate to become highly inaccurate. the goals of this paper are (i) to investigate the nature of this bias in VO, (ii) to propose methods of estimating it, and (iii) to provide a correction that can potentially be used online. We identify two effects at play in stereo VO bias: first, the inherent bias in the maximum-likelihood estimation framework, and second, the disparity threshold used to discard far-away and erroneous stereo observations. In order to estimate the bias, we investigate three methods: Monte Carlo sampling, the sigma-point method (with modification), and an existing analytical method in the literature. Based on simulations, we show that our new sigma-point method achieves similar accuracy to Monte Carlo, but at a fraction of the computational cost. Finally, we develop a bias correction algorithm by adapting the idea of the bootstrap in statistics, and demonstrate that our bias correction algorithm is capable of reducing approximately 95% of bias in VO problems without incorporating other sensors into the setup.

关键词： Cameras Estimation Feature extraction Monte Carlo methods Noise Noise measurement Visualization Motion and Path Planning Visual Navigation

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vision-based gesture recognition system for human-computer interaction 4th

Vision-based gesture recognition system for human-computer i...

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4th Eccomas thematic conference on Computational vision and Medical Image Processing (VipIMAGE)

作者： Trigueiros, Paulo Ribeiro, Fernando Reis, Luis Paulo IPP Oporto Portugal Univ Minho EEUM DSI Guimaraes Portugal

ISBN: (纸本)9781138000810

Hand gesture recognition, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. this is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. this work intends to study and implement a solution, generic enough, able to interpret user commands, composed of a set of dynamic and static gestures, and use those solutions to build an application able to work in a real-time human-computer interaction systems. the proposed solution is composed of two modules controlled by a FSM (Finite State Machine): a real time hand tracking and feature extraction system, supported by a SVM (Support Vector Machine) model for static hand posture classification and a set of HMMs (Hidden Markov Models) for dynamic single stroke hand gesture recognition. the experimental results showed that the system works very reliably, being able to recognize the set of defined commands in real-time. the SVM model for hand posture classification, trained with the selected hand features, achieved an accuracy of 99,2%. the proposed solution as the advantage of being computationally simple to train and use, and at the same time generic enough, allowing its application in any robot/system command interface.

关键词： Human-computer Interaction Gesture Recognition SVM ANN HMM FSM

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A Dual-arm Cooperating Physiotherapy Service robot Based on Visual Position

A Dual-arm Cooperating Physiotherapy Service Robot Based on ...

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4th International conference on Applied Mechanics and Mechanical Engineering (ICAMME 2013)

作者： Gao, Huanbing Lu, Shouyin Wang, Tao Shandong Univ Sch Control Sci & Engn Jinan 250100 Peoples R China Shandong Jianzhu Univ Sch Informat & Elect Engn Jinan Peoples R China

ISBN: (纸本)9783037859230

this paper presents the scheme of a physiotherapy service robot including the mechanical architecture, control system, visual position system, etc. the robot can treat degenerative disease and chronic disease of middle-aged and aged people by Chinese massage skill, the main body of which includes a massage adjustable bed, two 4-DOF robot arms and two massage hands that can accomplish various massage manipulations. Two arms cooperate to improve the massage efficiency, and provide sufficient strength and enough reachable workspace for massage. the manipulators are controlled by a TRIO multi-axes motion controller and a embedded computer module. Physiological signal and massage pressure is detecting in real time in massage process to ensure a scientific and safe therapy. vision System sends the recognized acupoint position to the master system to track the patient's body, and the acupoint being massaged is displayed in real time by the 3D virtual display model. the robot can execute ten massage manipulations, which make traditional Chinese massage can have a robot instead. the effectiveness for degenerative lumbago in middle-aged and aged is demonstrated by laboratory examination and clinical trial.

关键词： Acupoint recognition Motion control Physiological signal detecting

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Towards embedded robot vision for multi-scale object recognition repeatability of interest points detected in half-octave binomial pyramids

Towards embedded robot vision for multi-scale object recogni...

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4th International conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2014

作者： Entschev, Peter Andreas Neto, Hugo Vieira Graduate School of Electrical Engineering and Applied Computer Science Federal University of Technology Paranà Avenida Sete de Setembro 3165 Curitiba Brazil

ISBN: (纸本)9789897580000

the construction of multi-scale image pyramids is used in state-of-the-art methods that perform robust object recognition, such as SIFT and SURF. However, building such image pyramids is computationally expensive, especially when implementations in embedded systems with limited computing resources are considered. therefore, the use of alternative less expensive approaches are necessary if near real-time operation is desired. Previous work has reported that using binomial filters to construct half-octave multi-scale pyramids consumes only 1=4 of the processing time of the Gaussian pyramid originally used in the SIFT framework. Here we investigate how interest points detected using the binomial approach behave when compared to the Gaussian approach, focusing on repeatability. Experimental results show that in average up to 86% of interest points detected with the original SIFT pyramid building scheme are also detected when using the binomial method, despite of large gains in processing time. When rotation of image features is considered, experimental results demonstrate that slightly superior repeatability of interest points is achieved using the binomial pyramid.

关键词： Object recognition

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