Onur Tekdas

Using mobile robots to harvest data from sensor fields

We explore synergies among mobile robots and wireless sensor networks in environmental monitoring through a system in which robotic data mules collect measurements gathered by sensing nodes. A proof-of-concept implementation demonstrates that this approach significantly increases the lifetime of the system by conserving energy that the sensing nodes otherwise would use for communication.

Robotic Routers: Algorithms and Implementation

Mobile robots equipped with wireless networking capabilities can act as robotic routers and provide network connectivity to mobile users. Robotic routers provide cost-efficient solutions for the deployment of a wireless network in a large environment with a limited number of users. In this paper, we present motion planning algorithms for robotic routers to maintain the connectivity of a single user to a base station. We consider two motion models for the user. In the first model, the user’s motion is known in advance. In the second model, the user moves in an adversarial fashion and tries to break the connectivity. We present optimal motion planning strategies for both models. We also present details of a proof-of-concept implementation.

Sensor Placement for Triangulation-Based Localization

Robots operating in a workspace can localize themselves by querying nodes of a sensor-network deployed in the same workspace. This paper addresses the problem of computing the minimum number and placement of sensors so that the localization uncertainty at every point in the workspace is less than a given threshold. We focus on triangulation-based state estimation, where measurements from two sensors must be combined for an estimate. This problem is NP-hard in its most general from. For the general version, we present a solution framework based on integer linear programming and demonstrate its application in a fire-tower placement task. Next, we study the special case of bearing-only localization and present an approximation algorithm with a constant factor performance guarantee.

Sensor Placement Algorithms for Triangulation Based Localization

Robots operating in a workspace can localize themselves by querying nodes of a sensor-network deployed in the same workspace. This paper addresses the problem of computing the minimum number and placement of sensors so that the localization uncertainty at every point in the workspace is less than a given threshold. We focus on triangulation based state estimation where measurements from two sensors must be combined for an estimate. We show that the general problem for arbitrary uncertainty models is computationally hard. For the general problem, we present a solution framework based on integer linear programming and demonstrate its practical feasibility with simulations. Finally, we present an approximation algorithm for a geometric uncertainty measure which simultaneously addresses occlusions, angle and distance constraints.

Efficient data collection from wireless nodes under the two-ring communication model

We introduce a new geometric robot-routing problem which arises in data-muling applications where a mobile robot is charged with collecting data from stationary sensors. The objective is to compute the robot’s trajectory and download sequence so as to minimize the time to collect data from all of the sensors. The total data collection time has two components:the robot’s travel time and the download time. The time to download data from a sensor s is a function of the location of the robot and s: if the robot is a distance r in away from s, it can download the sensor’s data in T in units of time. If the distance is greater than r in but less than r out , the download time is T out > T in . Otherwise, the robot can not download the data from s. Here, r in , r out , T in and T out are input parameters. We refer to this model, which is based on recently developed experimental models for sensor network deployments, as the two-ring model, and the problem of downloading data from a given set of sensors in minimum amount of time under this model as the two-ring tour (TRT) problem. We present approximation algorithms for the general case which uses solutions to the traveling salesperson with neighborhoods (TSPN) Problem as subroutines. We also present effcient solutions to special, but practically important versions of the problem such as grid-based and sparse deployments. The approach is validated in outdoor experiments.

Maintaining connectivity in environments with obstacles

Robotic routers (mobile robots with wireless communication capabilities) can create an adaptive wireless network and provide communication services for mobile users on-demand. Robotic routers are especially appealing for applications in which there is a single mobile user whose connectivity to a base station must be maintained in an environment that is large compared to the wireless range. In this paper, we study the problem of computing motion strategies for robotic routers in such scenarios, as well as the minimum number of robotic routers necessary to enact our motion strategies. Assuming that the routers are as fast as the user, we present an optimal solution for cases where the environment is a simply-connected polygon, a constant factor approximation for cases where the environment has a single obstacle, and an O(h) approximation for cases where the environment has h circular obstacles. The O(h) approximation also holds for cases where the environment has h arbitrary polygonal obstacles, provided they satisfy certain geometric constraints - e.g. when the set of their minimum bounding circles is disjoint.

Building a Communication Bridge with Mobile Hubs

We study scenarios where mobile hubs are charged with building a communication bridge between two given points s and t. We introduce a new bi-criteria optimization problem where the objectives are minimizing the number of hubs on the bridge and either the maximum or the total distance traveled by the hubs. For a geometric version of the problem where the hubs must move onto the line segment [s,t], we present algorithms which achieve the minimum number of hubs while remaining within a constant factor of a given motion constraint.

Energy-Efficient Data Collection from Wireless Nodes Using Mobile Robots

This work focuses on systems where mobile robots periodically collect data from (static) wireless sensor network nodes. Suppose we are given approximate locations of the static nodes, and an order with which the robot will visit these nodes. We present solutions to the following problems. (i) From the static node’s perspective: given the stochastic nature of the robot’s arrival, what is an energy-efficient strategy to send beacon messages? Such a strategy must simultaneously minimize the robot’s waiting time and the number of beacon messages. (ii) From the robot’s perspective: given the stochastic nature of the wireless link quality, what is an energy-efficient motion strategy to find a good pose (location and orientation) from where the data can be downloaded efficiently? The robot must be able to find such a location quickly but without taking too many measurements so as to conserve the static node’s energy.