Sameera Poduri

Constrained coverage for mobile sensor networks

We consider the problem of self-deployment of a mobile sensor network. We are interested in a deployment strategy that maximizes the area coverage of the network with the constraint that each of the nodes has at least K neighbors, where K is a user-specified parameter. We propose an algorithm based on artificial potential fields which is distributed, scalable and does not require a prior map of the environment. Simulations establish that the resulting networks have the required degree with a high probability, are well connected and achieve good coverage. We present analytical results for the coverage achievable by uniform random and symmetrically tiled network configurations and use these to evaluate the performance of our algorithm.

Energy-quality tradeoffs for target tracking in wireless sensor networks

We study the tradeoffs involved in the energy-efficient localization and tracking of mobile targets by a wireless sensor network. Our work focuses on building a framework for evaluating the fundamental performance of tracking strategies in which only a small portion of the network is activated at any point in time. We first compare naive network operation with random activation and selective activation. In these strategies the gains in energy-savings come at the expense of increased uncertainty in the location of the target, resulting in reduced quality of tracking. We show that selective activation with a good prediction algorithm is a dominating strategy that can yield orders-of-magnitude energy savings with negligible difference in tracking quality. We then consider duty-cycled activation and show that it offers a flexible and dynamic tradeoff between energy expenditure and tracking error when used in conjunction with selective activation.

Using Local Geometry for Tunable Topology Control in Sensor Networks

Neighbor-Every-Theta (NET) graphs are such that each node has at least one neighbor in every theta angle sector of its communication range. We show that for thetas < pi, NET graphs are guaranteed to have an edge-connectivity of at least floor (2pi)/thetas, even with an irregular communication range. Our main contribution is to show how this family of graphs can achieve tunable topology control based on a single parameter thetas. Since the required condition is purely local and geometric, it allows for distributed topology control. For a static network scenario, a power control algorithm based on the NET condition is developed for obtaining k-connected topologies and shown to be significantly efficient compared to existing schemes. In controlled deployment of a mobile network, control over positions of nodes can be leveraged for constructing NET graphs with desired levels of network connectivity and sensing coverage. To establish this, we develop a potential fields based distributed controller and present simulation results for a large network of robots. Lastly, we extend NET graphs to 3D and provide an efficient algorithm to check for the NET condition at each node. This algorithm can be used for implementing generic topology control algorithms in 3D.

Coarse In-building Localization with Smartphones ?

Geographic location of a person is important contextual information that can be used in a variety of scenarios like disaster relief, directional assistance, context-based advertisements, etc. GPS provides accurate localization outdoors but is not useful inside buildings. We propose an coarse indoor localization ap- proach that exploits the ubiquity of smart phones with embedded sensors. GPS is used to find the building in which the user is present. The Accelerometers are used to recognize the users dynamic activities (going up or down stairs or an elevator) to determine his/her location within the building. We demonstrate the ability to estimate the floor-level of a user. We compare two techniques for activ- ity classification, one is naive Bayes classifier and the other is based on dynamic time warping. The design and implementation of a localization application on the HTC G1 platform running Google Android is also presented.

Achieving connectivity through coalescence in mobile robot networks

Coalescence is the problem of isolated mobile robots independently searching for peers with the goal of forming a single connected network. This paper analyzes coalescence time for a worst-case scenario where the robots do not have any knowledge about the environment or positions of other robots and perform independent, memoryless search. Using the random direction mobility model, we show that coalescence time has an exponential distribution which is a function of the number of robots, speed, communication range, and size of the domain. Further, as the number of robots (N) increases, coalescence time decreases as O(1/√N) and Ω(log(N)/N). Simulations validate our analysis and also suggest that the lower bound is tight. This paper is an extension of [1] where we studied a simplified setting with a stationary base station that the robots search for and coalesce to.

OCRdroid: A framework to digitize text using mobile phones

As demand grows for mobile phone applications, research in optical character recognition, a technology well developed for scanned documents, is shifting focus to the recognition of text embedded in digital photographs. In this paper, we present OCRdroid, a generic framework for developing OCR-based applications on mobile phones. OCRdroid combines a light-weight image preprocessing suite installed inside the mobile phone and an OCR engine connected to a backend server. We demonstrate the power and functionality of this framework by implementing two applications called PocketPal and PocketReader based on OCRdroid on HTC Android G1 mobile phone. Initial evaluations of these pilot experiments demonstrate the potential of using OCRdroid framework for real-world OCR-based mobile applications.

Mission design for compressive sensing with mobile robots

This paper considers mission design strategies for mobile robots whose task is to perform spatial sampling of a static environmental field, in the framework of compressive sensing. According to this theory, we can reconstruct compressible fields using O(log n) nonadaptive measurements (where n is the number of sites of the spatial domain), in a basis that is “incoherent” to the representation basis [1]; random uncorrelated measurements satisfy this incoherence requirement. Because an autonomous vehicle is kinematically constrained and has finite energy and communication resources, it is an open question how to best design missions for CS reconstruction. We compare a two-dimensional random walk, a TSP approximation to pass through random points, and a randomized boustrophedon (lawnmower) strategy. Not unexpectedly, all three approaches can yield comparable reconstruction performance if the planning horizons are long enough; if planning occurs only over short time scales, the random walk will have an advantage.

Distributed coverage control for mobile sensors with location-dependent sensing models

This paper addresses the problem of coverage control of a network of mobile sensors. In the current literature, this is commonly formulated as a locational optimization problem under the assumption that sensing performance is independent of the locations of sensors. We extend this work to a more general framework where the sensor model is location-dependent. We propose a distributed control law and coordination algorithm. If the global sensing performance function is known a priori, we prove that the algorithm is guaranteed to converge. To validate this algorithm, we conduct experiments with indoor and outdoor deployments of Cyclops cameras and model its sensing performance. This model is used to simulate deployments on 1D pathways and study the coverage obtained. We also examine the coverage in the case when the global sensing function is not known and is estimated in an online fashion.

Surrounding Nodes in Coordinate-Free Networks

Consider a network of nodes in the plane whose locations are unknown but which establish communication links based on proximity. We solve the following problems: given a node in the network, (1) determine if a given cycle surrounds the node; and (2) find some cycle that surrounds the node. The only localization capabilities assumed are unique IDs with binary proximity measure, and, in some cases, cyclic orientation of neighbors. We give complete algorithms for finding and verifying surrounding cycles when cyclic orientation data is available. We also provide an efficient but non-complete algorithm in the case where angular data is not available.

Latency Analysis of Coalescence for Robot Groups

Coalescence is the problem of isolated mobile robots independently searching for peers with the goal of forming a single connected network. This is important because communication is a necessary requirement for several collaborative robot tasks. In this paper, we consider a scenario where the robots do not have any information about the environment or positions of other robots and perform a random walk search. We show through probabilistic analysis that as the number of isolated robots N increases, the expected coalescence time decreases as 1/radicN. Simulations results are presented to validate this analysis.