Aplikasi Metoda Random Walks untuk Kontrol Gerak Robot Berbasis Citra

Algoritma merupakan bagian penting dalam sistem kontrol robot. Terdapat banyak metode yang biasa digunakan untuk keperluan ini, salah satunya adalah random walks. Metode ini menitikberatkan pada estimasi gerakan berdasarkan bilangan random (acak). Disisi lain aplikasi pengolahan citra masih belum banyak digunakan sebagai alat kontrol. Makalah ini akan membahas model dan simulasi metode random walks untuk kontrol gerak robot pada citra yang sederhana. Kata Kunci:random walks, citr

A Spectral Learning Approach to Range-Only SLAM

We present a novel spectral learning algorithm for simultaneous localization and mapping (SLAM) from range data with known correspondences. This algorithm is an instance of a general spectral system identification framework, from which it inherits several desirable properties, including statistical consistency and no local optima. Compared with popular batch optimization or multiple-hypothesis tracking (MHT) methods for range-only SLAM, our spectral approach offers guaranteed low computational requirements and good tracking performance. Compared with popular extended Kalman filter (EKF) or extended information filter (EIF) approaches, and many MHT ones, our approach does not need to linearize a transition or measurement model; such linearizations can cause severe errors in EKFs and EIFs, and to a lesser extent MHT, particularly for the highly non-Gaussian posteriors encountered in range-only SLAM. We provide a theoretical analysis of our method, including finite-sample error bounds. Finally, we demonstrate on a real-world robotic SLAM problem that our algorithm is not only theoretically justified, but works well in practice: in a comparison of multiple methods, the lowest errors come from a combination of our algorithm with batch optimization, but our method alone produces nearly as good a result at far lower computational cost

Global Localization of an Indoor Mobile Robot with a single Base Station

The navigation tasks in advanced home robotic applications incorporating reliable revisiting strategies are dependent on very low cost but nevertheless rather accurate localization systems. In this paper a localization system based on the principle of trilateration is described. The proposed system uses only a single small base station, but achieves accuracies comparable to systems using spread beacons and it performs sufficiently for map building. Thus it is a standalone system and needs no odometry or other auxiliary sensors. Furthermore a new approach for the problem of the reliably detection of areas without direct line of sight is presented. The described system is very low cost and it is designed for use in indoor service robotics. The paper gives an overview on the system concept and special design solutions and proves the possible performances with experimental results

[[alternative]]Low Power SoC Design for Adaptive Robot Vision System(I)

計畫編號：NSC96-2218-E032-003研究期間：200708~200807研究經費：777,000[[abstract]]機器人視覺為機器人系統中一個非常重要的關鍵，機器人必須使用機器人視覺來作 空間定位、標的物辨識，目標距離估測、以及標的物座標判定，因此機器人視覺系統可 說是機器人系統的靈魂。本研究計畫主要目的是要研製一個供人形機器人足球員使用的 視覺系統，以利此人形機器人進行「ROBOT CUP」與「FIRA CUP」國際機器人足球員 競賽之所需。在「ROBOT CUP」與「FIRA CUP」國際機器人足球員競賽中，機器人必 須具備踢球、避障、行進崎嶇路段、對抗、…等功能，因此對視覺之需求非常殷切。我 們計劃以CMOS 感測器為本機器人視覺系統的視覺感測器，這個機器人視覺系統必須 具備許多技術，例如：空間定位技術、色彩辨識技術，物件分割技術、移動估測、距離 估測等。根據這些技術來判斷周圍環境之影響，這些判斷都有即時性，因此需要以硬體 方式加以實現；此外，機器人之體積容量有限，因此無法容納太大的硬體基板，所以此 機器人視覺系統必須以積體電路化(IC)來實現，由於此機器人視覺系統複雜度頗高，因 此本研究計畫最後將會以系統晶片(System on Chip, SOC)方式實現此機器人視覺系統。 本研究計畫為一個三年期之研究計畫，第一年的研究主題為機器人視覺的技術開 發，其中以進階影像處理技術為主，研發快速視覺處理之演算法，將所開發之演算法加 以硬體架構化，並以FPGA 平台來驗證。第二年之研究主題將針對第一年研發之演算法 以SOC 方式加以實現，並以低功率(Low Power)及低成本(Low Cost)為目標。第三年除 了將所製作出來的機器人視覺晶片整合於總計畫之人形機器人中外，我們將進一步對機 器人雙眼視覺加以研究，希望對機器人視覺作進一步的改良。[[sponsorship]]行政院國家科學委員

Enlightened shelf awareness

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.Includes bibliographical references (p. 52-55).The use of RFID technology in libraries has increased to the point where it is now the centerpiece of emerging automated self-checkout, return, and theft detection systems. With the external borders of the library secure, focus has shifted to improve the internal state of a library's collection, which is subjected daily to use and abuse by library patrons. In this thesis I present BookBot, a robot equipped with RFID readers, that automates the otherwise manual shelf-reading process and helps librarians keep their database in sync with the library's physical inventory. Experiments on single shelves and entire bookcases confirm that this robot-assisted approach to inventory management can not only detect misplaced books reliably, but accurately determine the order of the books on the shelves and even localize the coordinates of each book to within a few centimeters, enabling both the librarian and the user to reach a state of Enlightened Shelf Awareness.by Isaac M. Ehrenberg.S.M

Cooperative Navigation for Low-bandwidth Mobile Acoustic Networks.

This thesis reports on the design and validation of estimation and planning algorithms for underwater vehicle cooperative localization. While attitude and depth are easily instrumented with bounded-error, autonomous underwater vehicles (AUVs) have no internal sensor that directly observes XY position. The global positioning system (GPS) and other radio-based navigation techniques are not available because of the strong attenuation of electromagnetic signals in seawater. The navigation algorithms presented herein fuse local body-frame rate and attitude measurements with range observations between vehicles within a decentralized architecture. The acoustic communication channel is both unreliable and low bandwidth, precluding many state-of-the-art terrestrial cooperative navigation algorithms. We exploit the underlying structure of a post-process centralized estimator in order to derive two real-time decentralized estimation frameworks. First, the origin state method enables a client vehicle to exactly reproduce the corresponding centralized estimate within a server-to-client vehicle network. Second, a graph-based navigation framework produces an approximate reconstruction of the centralized estimate onboard each vehicle. Finally, we present a method to plan a locally optimal server path to localize a client vehicle along a desired nominal trajectory. The planning algorithm introduces a probabilistic channel model into prior Gaussian belief space planning frameworks. In summary, cooperative localization reduces XY position error growth within underwater vehicle networks. Moreover, these methods remove the reliance on static beacon networks, which do not scale to large vehicle networks and limit the range of operations. Each proposed localization algorithm was validated in full-scale AUV field trials. The planning framework was evaluated through numerical simulation.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/113428/1/jmwalls_1.pd

A parallel hypothesis method of autonomous underwater vehicle navigation

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2009This research presents a parallel hypothesis method for autonomous underwater vehicle navigation that enables a vehicle to expand the operating envelope of existing long baseline acoustic navigation systems by incorporating information that is not normally used. The parallel hypothesis method allows the in-situ identification of acoustic multipath time-of-flight measurements between a vehicle and an external transponder and uses them in real-time to augment the navigation algorithm during periods when direct-path time-of-flight measurements are not available. A proof of concept was conducted using real-world data obtained by the Woods Hole Oceanographic Institution Deep Submergence Lab's Autonomous Benthic Explorer (ABE) and Sentry autonomous underwater vehicles during operations on the Juan de Fuca Ridge. This algorithm uses a nested architecture to break the navigation solution down into basic building blocks for each type of available external information. The algorithm classifies external information as either line of position or gridded observations. For any line of position observation, the algorithm generates a multi-modal block of parallel position estimate hypotheses. The multimodal hypotheses are input into an arbiter which produces a single unimodal output. If a priori maps of gridded information are available, they are used within the arbiter structure to aid in the elimination of false hypotheses. For the proof of concept, this research uses ranges from a single external acoustic transponder in the hypothesis generation process and grids of low-resolution bathymetric data from a ship-based multibeam sonar in the arbitration process. The major contributions of this research include the in-situ identification of acoustic multipath time-of-flight measurements, the multiscale utilization of a priori low-resolution bathymetric data in a high-resolution navigation algorithm, and the design of a navigation algorithm with a exible architecture. This flexible architecture allows the incorporation of multimodal beliefs without requiring a complex mechanism for real-time hypothesis generation and culling, and it allows the real-time incorporation of multiple types of external information as they become available in situ into the overall navigation solution

Wireless sensor data processing for on-site emergency response

This thesis is concerned with the problem of processing data from Wireless Sensor Networks (WSNs) to meet the requirements of emergency responders (e.g. Fire and Rescue Services). A WSN typically consists of spatially distributed sensor nodes to cooperatively monitor the physical or environmental conditions. Sensor data about the physical or environmental conditions can then be used as part of the input to predict, detect, and monitor emergencies. Although WSNs have demonstrated their great potential in facilitating Emergency Response, sensor data cannot be interpreted directly due to its large volume, noise, and redundancy. In addition, emergency responders are not interested in raw data, they are interested in the meaning it conveys. This thesis presents research on processing and combining data from multiple types of sensors, and combining sensor data with other relevant data, for the purpose of obtaining data of greater quality and information of greater relevance to emergency responders. The current theory and practice in Emergency Response and the existing technology aids were reviewed to identify the requirements from both application and technology perspectives (Chapter 2). The detailed process of information extraction from sensor data and sensor data fusion techniques were reviewed to identify what constitutes suitable sensor data fusion techniques and challenges presented in sensor data processing (Chapter 3). A study of Incident Commanders’ requirements utilised a goal-driven task analysis method to identify gaps in current means of obtaining relevant information during response to fire emergencies and a list of opportunities for WSN technology to fill those gaps (Chapter 4). A high-level Emergency Information Management System Architecture was proposed, including the main components that are needed, the interaction between components, and system function specification at different incident stages (Chapter 5). A set of state-awareness rules was proposed, and integrated with Kalman Filter to improve the performance of filtering. The proposed data pre-processing approach achieved both improved outlier removal and quick detection of real events (Chapter 6). A data storage mechanism was proposed to support timely response to queries regardless of the increase in volume of data (Chapter 7). What can be considered as “meaning” (e.g. events) for emergency responders were identified and a generic emergency event detection model was proposed to identify patterns presenting in sensor data and associate patterns with events (Chapter 8). In conclusion, the added benefits that the technical work can provide to the current Emergency Response is discussed and specific contributions and future work are highlighted (Chapter 9)