Abstract

This paper deals with the tracking and following of a person with a camera mounted mobile robot. A modified energy based optical flow approach is used for motion segmentation from a pair of images. Further a spatial relative veolcity based filering is used to extract prominently moving objects. Depth and color information are also used to robustly identify and follow a person.

Abstract

This paper explains how to singularize a robot to a unique hypothesis state from a state of multiple hypotheses. This it does by computing a path whose expected distance is minimum from a tree where each path to the leaf from the root results in a singular hypothesis. At various nodes of the tree the number of hypotheses is reduced as it proceeds down from the root. The nodes of the tree are computed as the best locations to move from an earlier higher hypotheses state. They are either frontier regions or a direction of traversal that result in reduction of hypotheses from an earlier multi hypotheses state. The method has been tested robustly in various simulation situations and its efficacy confirmed.

Abstract

We present a method for finding reduced time coverage paths of multiple UAVs (Unmanned Air Vehicles) monitoring a 3D terrain represented as height fields. A novel metric based on per time visibility is used that couples visibility gained at a terrain point with the time spent to reach the point. This coupled metric is utilized to form reduced time paths by maximizing the visibility gained per unit time at every step. We compare the results of this approach with an approach that covers the terrain based on a per distance visibility metric, which reduces the sum, over distances covered by each UAV path. The comparisons show that the current method gives substantially time reduced paths albeit with an expected increase in sum over distances of UAV paths. We also show that time taken to cover the terrain based on the current metric is far less than prevalent methods that try to decompose the terrain based on visibility followed by time or time followed by visibility in a decoupled fashion. The method is further extended to provide for fault tolerance on a hostile terrain. Each terrain point is guaranteed to be seen by at-least one UAV that has not been damaged due to any calamity, shot or otherwise.

Abstract

To improve the mobility of wheeled robots traversing on and uneven terrain having slopes in all three orthogonal directions is the primary focus of our research. Past research on ‘all terrain vehicles’,[1],[2], was focused on developing mechanical suspension systems which could improve terrain adaptability and locomotion. Consequently control algorithms were developed for posture stability of the vehicle [3],[4]. Shrimp robots [1] and Rocky rovers [2] are terrain vehicles with passive suspension systems which have excellent terrain adaptability and ability to negotiate terrains having discontinuities that are higher than the wheel radius. But mobility and stability of such vehicles is not guaranteed. Thus for such conditions Sreenivasan and Waldron [4] developed vehicles called Wheeled and Actively Articulated Vehicles

Abstract

This paper presents a novel real-time algorithm to sequentially solve the triangulation problem. The problem addressed is estimation of 3D point coordinates given its images and the matrices of the respective cameras used in the imaging process. The algorithm has direct application to real time systems like visual SLAM. This article demonstrates the application of the proposed algorithm to the mapping problem in visual SLAM. Experiments have been carried out for the general triangulation problem as well as the application to visual SLAM. Results show that the application of the proposed method to mapping in visual SLAM outperforms the state of the art mapping methods.

Abstract

In environments which possess relatively few features that enable a robot to unambiguously determine its location, global localization algorithms can result in multiple hypotheses locations of a robot. In such a scenario the robot, for effective localization, has to be actively guided to those locations where there is a maximum chance of eliminating most of the ambiguous states - which is often referred to as dasiaactive localizationpsila. When extended to multi robotic scenarios where all robots possess more than one hypothesis of their position, there is the opportunity to do better by using robots apart from obstacles as dasiahypotheses resolving agentspsila. The paper presents a unified framework accounting for the map structure as well as measurement amongst robots while guiding a set of robots to locations where they can singularize to a unique state. The appropriateness of our approach is demonstrated empirically in both simulation & real-time (on Amigobots) and its efficacy verified. Extensive comparative analysis portrays the advantage of the current method over others that do not perform active localization in a multi-robotic sense.

Abstract

We present a method for finding paths for multiple unmanned air vehicles (UAVs) such that the sum over their lengths is minimum as they cover a 3D terrain (represented as height fields). The paths are constrained to lie beneath an exposure surface to ensure stealth from enemy outposts. The exposure surface is also computed as a height field. The algorithm greedily clusters the terrain such that gain in visibility per distance would be higher for intra-cluster points than points across clusters. Paths generated on clusters formed by such a per distance visibility metric are reduced by more than 25% over other related decoupled methods. The method is extended to cover terrains with partial visibilities. The advantage of the coupled metric extends under constrained visibility also. We again show performance gain by comparing with an existing decoupled algorithm that solves a similar problem of minimum distance terrain coverage with constrained visibility. The paper reveals that decomposing the terrain based on visibility first and then distance is always better than the other way round to cover the terrain in shorter distances.

Abstract

Intermodal (IM) trains are typically the fastest freight trains operated in North America. The aerodynamic characteristics of many of these trains are often relatively poor resulting in high fuel consumption. However, considerable variation in fuel efficiency is possible depending on how the loads are placed on railcars in the train. Consequently, substantial potential fuel savings are possible if more attention is paid on the loading configurations of trains. A wayside machine vision (MV) system was developed to automatically scan passing IM trains and assess their aerodynamic efficiency. MV algorithms are used to analyse these images, detect and measure gaps between loads. In order to make use of the data, a scoring system was devel- oped based on two attributes – the aerodynamic coefficient and slot efficiency. The aerodynamic coefficient is calculated using the Aerodynamic Subroutine of the Train Energy Model. Slot effi- ciency represents the difference between the actual and ideal loading configuration given the particular set of railcars in the train. This system can provide IM terminal managers feedback on loading performance for trains and be integrated into the software support systems used for loading assignment.

Abstract

Controlling molecular energetics using laser pulses is exemplified for nuclear motion in two different diatomic systems. The problem of finding the optimized field for maximizing a desired quantum dynamical target is formulated using an iterative method. The method is applied for two diatomic sys- tems, HF and OH. The power spectra of the fields and evolution of populations of different vibrational states during transitions are obtained.

Abstract

Binding of Gold Nanoclusters with Size-Expanded DNA Bases: A Computational Study of Structural and Electronic Properties Purshotam Sharma, Himanshu Singh, Sitansh Sharma, and Harjinder Singh* Center for Computational Natural Sciences and Bioinformatics, International Institute of Information and Technology, Gachibowli, Hyderabad-500032, India Received June 15, 2007 Abstract: Binding of gold nanoclusters with size-expanded DNA bases, xA, xC, xG, and xT, is studied using quantum chemical methods. Geometries of the neutral xA-Au6, xC-Au6, xG-Au6, and xT-Au6 complexes were fully optimized using the B3LYP density functional method (DFT). The gold clusters around xA and xT adopt triangular geometries, whereas irregular structures are obtained in the case of gold clusters complexed around xC and xG. The lengths of the bonds between atoms in the x-bases increase on gold complexation. The aromatic character of the x-bases also increases on gold complexation except for the five-member rings. A significant charge transfer from the x-base to gold atoms is seen in these complexes. Second-order interactions are observed in addition to direct covalent bonds between gold atoms and x-bases.