Abstract

IISc Bangalore has developed a recognition engine for Tamil printed text, which has been tested on 1000 document images of pages scanned from books printed between 1950 and 2000. IIIT Hyderabad has developed a XML based annotated database for storing the 5000 images of scanned pages and the corresponding typed text in Unicode. CDAC, Noida has developed an efficient evaluation tool, which compares the OCR output text to the reference typed text (ground truth) and flashes the substitution, deletion and insertion errors in different colours on the screen, so that the design team can quickly identify the issues with the OCR and make corrective steps for improving the performance. IIT Delhi has proposed and developed a novel scheme for segmenting only the text regions from document images containing pictures. The OCRs uses Karhunen-Louve transform (KLT) as features and a support vector machine (SVM) classifier with RBF kernel in a discriminative directed acyclic graph (DDAG) configuration. They assume an uncompressed input image of the document page, scanned at a minimum of 300 dpi with 256 gray levels (not binary or two-level). Tamil OCR currently gives over 94% recognition accuracy at the Unicode level, evaluated on over 1000 printed pages, some of them also containing old Tamil letters.

Abstract

Prediction of electric load is very important issue for modern day power system engineers and a very good day ahead prediction of electric load is required for efficient performance of various Energy Management System (EMS) functions such as unit commitment, economic dispatch, fuel scheduling, and unit maintenance. A fuzzy based approach for day ahead prediction of electric load using Mahalanobis distance has been chosen in this work. Mahalanobis distance provides the similar characteristic days from the historical data set based on some independent variables generally of climate and time (such as temperature, day of the week, month etc.) and that are used to predict the dependent variable, i.e., day ahead electric load demand. The independent variables considered for the distance measure include the hourly humidity values, hourly temperatures values, and the day type variable.The similarity between the load on the day of prediction and that on similar characteristic days, which is evaluated using fuzzy system

Abstract

Incorporating ferromagnetic materials into integrated microwave devices is a promising approach for the development of on-chip high-performance circuit components. Therefore, high-frequency domain-wall motion and magnetization rotation, which yield permeability, are of primary interest. However, so far it has not been attempted to physically separate high-frequency domain-wall motion and magnetization rotation driven by external magnetic field excitation. Nor have attempts for the corresponding characterizations. In this work, patterned permalloy films are integrated with on-chip microstrip lines. Domain-wall motion and magnetization rotation are separated through aspect ratio and dimension control. The measured results show that high-frequency-field driven domain-wall motion is fast, different from current driven domain-wall motion. It is also shown that coupling effects are not important when the distance between two adjacent permalloy films is~ 1 μm despite their large lateral dimensions. Finally, surface topography affects domain structures and corresponding dynamic processes.

Abstract

In this paper we deduce the evolution of a four wheeled active suspension rover from a five wheeled passive suspension rover. The aim of this paper is to design a suspension mechanism which utilizes the advantages of both passive suspension and active suspension rover. Both the design considered here are simpler than the existing suspension mechanisms in the sense that the number of links as wells as the number of joints have been significantly reduced without compromising the climbing capability of the rover. We first analyze the kinematics of the five wheeled rover and its motion pattern while climbing an obstacle and try to deduce the same motion pattern and capability in the four wheeled rover. Both the suspension mechanism consists of two planar closed kinematic chains on each side of the rover. We also deduce the control strategy for the active suspension rover wherein only two actuators are used to control the internal configuration of the rover. To the best of author's knowledge this is the minimum number of actuators required to control the internal configuration of a active suspension while operating on a fully 3D rough terrain. Extensive uneven terrain simulations are performed for both 5-wheeled and 4-wheeled rover and a comparative analysis has been done on maximum coefficient of friction and torque requirements.

Abstract

The ability to detect, and track multiple moving objects like person and other robots, is an important prerequisite for mobile robots working in dynamic indoor environments. We approach this problem by detecting independently moving objects in image sequence from a monocular camera mounted on a robot. We use multi-view geometric constraints to classify a pixel as moving or static. The first constraint, we use, is the epipolar constraint which requires images of static points to lie on the corresponding epipolar lines in subsequent images. In the second constraint, we use the knowledge of the robot motion to estimate a bound in the position of image pixel along the epipolar line. This is capable of detecting moving objects followed by a moving camera in the same direction, a so-called degenerate configuration where the epipolar constraint fails. To classify the moving pixels robustly, a Bayesian framework is used to assign a probability that the pixel is stationary or dynamic based on the above geometric properties and the probabilities are updated when the pixels are tracked in subsequent images. The same framework also accounts for the error in estimation of camera motion. Successful and repeatable detection and pursuit of people and other moving objects in realtime with a monocular camera mounted on the Pioneer 3DX, in a cluttered environment confirms the efficacy of the method.

Abstract

In environments with identical features, the global localization of a robot, might result in multiple hypotheses of its location. If the situation is extrapolated to multiple robots, it results in multiple hypotheses for multiple robots. The localization is facilitated if the robots are actively guided towards locations where it can use other robots as well as obstacles to localize itself. This paper aims at presenting a learning technique for the above process of active localization of multiple robots by co-operation. An MDP framework is used for learning the task, over a semi-decentralized team of robots hereby maintaining a bounded complexity as opposed to various multi-agent learning techniques, which scale exponentially with the increase in the number of robots.

Abstract

We present efficient measurement models for localization in a feature based EKF SLAM framework. Both points and segments form the features, points include corners formed by intersection of wall like segments. The point features are described by its coordinates, while the segment feature is represented by the angle made by the normal to the segment from the global origin with the abscissa called the normal angle or N-angle for short. The measurement equation involves measuring the distance and bearing to the point feature and only bearing to the line feature. The distance measurement to the segment is intentionally kept out of the measurement equation due to its inefficacy in correcting the robot and landmarks state. This arises due to very large differences in the predicted and observed distances even for modest measurement errors when the robot is not very near the segment. Hence for this reason the segment feature is represented only by its N-angle devoid of distance since such a representation results in better state correction. The number of computations resulting from the covariance matrix updates is also less than a representation that includes both N-distance and N-angle.

Abstract

We present a method for extracting ground and other planes from a single non rotating laser mounted on a slow moving car used for on-road driving. A laser scan is decomposed into linear clusters. Corresponding clusters from subsequent scans are merged to form planes. The ground plane is identified based on the current vehicle height and the variance in height of the planes. Once these seed planes are identified future scan points either get associated with these planes or result in formation of new planes. Scan points that do not belong to any of the plane are left as such in the representation. Since the robustness of the method is contingent on how a single scan is decomposed into linear clusters, we compare the quality of the terrain representation due to three such clustering methods, one by iterative end point fit, other by adaptive breakpoint detection and thirdly the current method based on adaptive cosine similarity.

Abstract

We present a fast multi-robotic exploration methodology for 2D and 3D terrains. An asynchronous exploration strategy is introduced which shows significant improvements over the existing synchronous ones. A per-time visibility metric is being utilized by the algorithm. The metric allots the same weight for points for next view whose visibility over time ratios are equal. The outcome of this is that while the number of points visited to explore a terrain is nearly the same as other popular metrics found in literature, the time length of the paths are smaller in this case resulting in reduced time exploration. The results have been verified through extensive simulations in 2D and 3D. In 2D multiple robots explore unknown terrains that are office like, cluttered, corridor like and various combinations of these. In 3D we consider the case of multiple UAVs exploring a terrain represented as height fields. We introduce a way for calculating expected visibilities and a way of incorporating explored features in the per-time metric. The maximum height of the UAV at each location is governed by the so called exposure surface, beneath which the UAVs are constrained to fly. We also show performance gain of the present metric over others in experiments on a Pioneer 3DX robot.

Abstract

The objective of this work is to characterize certain important features of excitation of speech, namely, detecting the regions of glottal activity and estimating the strength of excita-tion in each glottal cycle. The proposed method is based on the assumption that the excitation to the vocal-tract system can be ap- proximated by a sequence of impulses of varying strengths. The effect due to an impulse in the time-domain is spread uniformly across the frequency-domain including at zero-frequency. We propose the use of a zero-frequency resonator to extract the characteristics of excitation source from speech signals by filtering out most of the time-varying vocal-tract information. The regions of glottal activity and the strengths of excitation estimated from the speech signal are in close agreement with those observed from the simultaneously recorded electro-glotto-graph signals. The performance of the proposed glottal activity detection is evaluated under different noisy environments at varying levels of degradation.