Improving communication in networked systems using mobile robots.

University of Minnesota Ph.D. dissertation. June 2011. Major: Computer science. Advisor: Prof. Ibrahim Volkan Isler. 1 computer file (PDF); xx, 193 pages, appendix A.Providing network communication in large, complex environments is an important task with applications to maintaining connectivity with mobile users, environmental monitoring, emergency response, search and rescue, etc. Traditional approaches accomplish this task by deploying a static wireless network over the entire environment. However, this solution becomes cost ineffective when the area to be covered is large. Recent advances in robotics technology and research have made it possible to build low-cost, robust mobile robots that can autonomously navigate in complex environments. Thanks to these advancements, it is now feasible to use robots as mobile network nodes in place of large static network deployments. However, in order to achieve good performance with a small number of robots, it is crucial to design efficient algorithms for planning the robots' paths. In this dissertation, we study the use of mobile robots in two specific networking applications. In the first application, we use mobile robots to provide communication between end-points that require a persistent connection in a large, complex environment. For instance, imagine that a mobile user in a large environment requests connectivity to a static base station. Since the service area of wireless routers is limited by their initial deployment locations, a static wireless network deployment requires many routers to fully cover the entire region. Alternatively, this drawback can be overcome by using a small number of robots as intermediate mobile routers between the user and the base station which adaptively maintain connectivity according to the user's movement. In the second application, we seek the use of mobile robots in delay-tolerant networks where a small delay in data transfer is acceptable. One such application is environmental monitoring where scientists collect statistical data such as soil temperature. The most crucial problem in this application is to gather the data from sensors which may be sparsely deployed over a large environment. We can avoid the inefficient use of intermediate relay nodes for data transfer by using mobile robots to autonomously collect the data from sensors. Since a small delay is tolerable, using a few robotic data carriers becomes an appealing solution. Our contributions in this dissertation are two-fold: on the theoretical front, we present path-planning algorithms with provable performance guarantees. First, we study the problem of maintaining the connectivity of a mobile end-point to a static end-point by using the minimum number of mobile routers. Second, we present solutions for creating a communication bridge between two static end-points by minimizing the number of robots and their movements. Third, we study the problem of finding robot paths so that robots collect data from sensors as quickly as possible. Lastly, we present strategies for robots which act as mobile sensors to efficiently monitor an environment. On the systems front, we implement our algorithms using mobile robots and demonstrate their practical feasibility through extensive experiments

Efficient Data Collection from Wireless Nodes under Two-Ring Communication Model

We introduce a new geometric 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 the data from all 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 locations 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 efficient solutions to special but practically important versions of the problem such as uniform and sparse deployment

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. </jats:p

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 &gt; 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. </jats:p

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 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