Islam I. Hussein

Effective Coverage Control for Mobile Sensor Networks With Guaranteed Collision Avoidance

This paper studies the problem of dynamically covering a given region in the plane using a set of mobile sensor agents. A novel problem formulation is proposed that addresses a number of important multiagent missions. The coverage goal, which is to cover a given search domain using multiple mobile sensors such that each point is surveyed until a certain preset level is achieved, is formulated in a mathematically precise problem statement. A control law is developed that guarantees to meet the coverage goal. This control law is modified to guarantee that a partially connected fleet also attains the coverage goal. Finally, a collision avoidance component is added to the controller to guarantee that the agents do not collide. The new controller is shown to safely achieve coverage. Several numerical examples are provided to illustrate the main results.

Optimal Control of Underactuated Nonholonomic Mechanical Systems

In this paper we use a nonholonomic affine connection formulation to study an optimal control problem for a class of nonholonomic, under-actuated mechanical systems. The class of nonholonomic systems we study in this paper includes, in particular, wheeled-type vehicles, which are important for many robotic locomotion systems. We illustrate our ideas by considering a simple example on a three-dimensional manifold

Awareness Coverage Control Over Large-Scale Domains With Intermittent Communications

In this paper a novel dynamic awareness coverage model is proposed and applied to coverage control over a large-scale task domain for a decentralized multi-vehicle sensor network with intermittent communications and possibly faulty sensors. For each vehicle, an individual state of awareness is defined. The individual vehicles state of awareness continuously evolves based on the vehicles motion and is updated at discrete instants whenever the vehicle establishes a new range- based communication link with other vehicles. This information sharing update step aides in reducing the amount of redundant coverage. In this paper we first consider the simplifying assumption where no awareness loss occurs when no sensors are monitoring portions of the domain. This scenario is applicable to some search and rescue/retrieval problems (especially with static victims or objects of interests), domain monitoring, and low level surveillance. Under this assumption, a decentralized control strategy is proposed that guarantees that every point within the task domain will be covered with a satisfactory state of awareness even under intermittent communications and/or faulty sensors. We demonstrate the effectiveness of the novel awareness model and decentralized control law via numerical simulations.

Estimation of Spatially Distributed Processes Using Mobile Spatially Distributed Sensor Network

The problem of estimating a spatially distributed process described by a partial differential equation (PDE), whose observations are contaminated by a zero mean Gaussian noise, is considered in this work. The basic premise of this work is that a set of mobile sensors achieve better estimation performance than a set of immobile sensors. To enhance the performance of the state estimator, a network of sensors that are capable of moving within the spatial domain is utilized. Specifically, such an estimation process is achieved by using a set of spatially distributed mobile sensors. The objective is to provide mobile sensor control policies that aim to improve the state estimate. The metric for such an estimate improvement is taken to be the expected state estimation error. Using different spatial norms, two guidance policies are proposed. The current approach capitalizes on the efficient filter gain design in order to avoid intense computational requirements resulting from the solution to filter Riccati equations. Simulation studies implementing and comparing the two proposed control policies are provided.

Real Time Feedback Control for Nonholonomic Mobile Robots With Obstacles

We introduce a method for constructing smooth feedback laws for a nonholonomic robot in a 2-dimensional polygonal workspace. First, we compute a smooth feedback law in the workspace without taking the nonholonomic constraints into account. We then give a general technique for using this to construct a new smooth feedback law over the entire 3-dimensional configuration space (consisting of position and orientation). The trajectories of the resulting feedback law will be smooth and will stabilize the position of the robot in the plane, neglecting the orientation. Our method is suitable for real time implementation and can be applied to dynamic environments

Effective Coverage Control using Dynamic Sensor Networks with Flocking and Guaranteed Collision Avoidance

This paper studies the problem of dynamically covering a given region D in R2 using a set of N mobile sensor agents. The coverage goal is to sample each point in the mission domain to a desired preset level. It is crucial in many dynamic coverage missions that the vehicles flock to guarantee reliable wireless communication links between the agents, while avoiding the risk of collisions. Dynamic coverage control strategies developed by the authors in their previous publications are modified for both flocking and guaranteed collision avoidance. Several numerical examples are provided to illustrate the main ideas.

Awareness coverage control over large scale domains with intermittent communications

In this paper a novel dynamic awareness coverage model is proposed and applied to coverage control over a large-scale task domain for a decentralized multi-vehicle sensor network with intermittent communications and possibly faulty sensors. For each vehicle, an individual state of awareness is defined. The individual vehicles state of awareness continuously evolves based on the vehicles motion and is updated at discrete instants whenever the vehicle establishes a new range- based communication link with other vehicles. This information sharing update step aides in reducing the amount of redundant coverage. In this paper we first consider the simplifying assumption where no awareness loss occurs when no sensors are monitoring portions of the domain. This scenario is applicable to some search and rescue/retrieval problems (especially with static victims or objects of interests), domain monitoring, and low level surveillance. Under this assumption, a decentralized control strategy is proposed that guarantees that every point within the task domain will be covered with a satisfactory state of awareness even under intermittent communications and/or faulty sensors. We demonstrate the effectiveness of the novel awareness model and decentralized control law via numerical simulations.

Cooperative Vision-Based Multi-Vehicle Dynamic Coverage Control for Underwater Applications

This paper studies the dynamic coverage control problem for underwater applications using a fleet of cooperative submarines with vision-based cameras. A sensor model for the vision-based camera is first presented. The coverage goal, which is to collect a desired amount of satisfactory quality samples at every point in a given domain, is stated in a precise mathematical statement. A coverage error function is then defined and used as a metric for the coverage quality. A gradient-descent control law is then derived. Numerical simulations are presented to illustrate the main results. Centralized and decentralized system architectures currently under investigation by the authors for an experimental test-bed are also discussed.

Dynamic sensor tasking for Space Situational Awareness

This paper examines the problem of tracking multiple spacecraft using a combination of ground- and space-based sensors. The problem is formulated in a simplified two-dimensional setting to reduce computational complexity while retaining elements of the problem that pose theoretical or practical difficulties (such as inverse square-law dynamics). As a baseline approach for comparison purposes, a centralized Extended Kalman Filter (EKF) estimator is used to provide position/velocity estimates of all tracked objects. These estimates and their associated covariances are used to execute a closed-loop sensor tasking approach to determine which sensors will track which objects. A tasking approach from the literature is utilized as a baseline methodology and compared to an ad-hoc modification which may offer improved performance in certain situations. The paper concludes with a numerical example demonstrating the approaches as well as a summary of avenues for future research.

Estimation of distributed processes using mobile spatially distributed sensors

In this paper we consider the problem of estimating a spatially distributed process described by a partial differential equation, which is also contaminated by a zero mean Gaussian noise. The estimation process is achieved using a set of spatially distributed mobile sensors. The objective is to provide sensor control policies that aim at improving the state estimate. The metric is taken to be the expected state estimation error. Using different spatial norms, two guidance policies are proposed. Simulation studies implementing and comparing the two proposed control policies are provided.