Renato C. Mesquita

Sensing and coverage for a network of heterogeneous robots

We address the problem of covering an environment with robots equipped with sensors. The robots are heterogeneous in that the sensor footprints are different. Our work uses the location optimization framework in with three significant extensions. First, we consider robots with different sensor footprints, allowing, for example, aerial and ground vehicles to collaborate. We allow for finite size robots which enables implementation on real robotic systems. Lastly, we extend the previous work allowing for deployment in non convex environments.

Simultaneous Coverage and Tracking (SCAT) of Moving Targets with Robot Networks

We address the problem of simultaneously covering an environment and tracking intruders (SCAT). The problem is translated to the task of covering environments with time-varying density functions under the locational optimization framework. This allows for coupling the basic subtasks: task assignment, coverage, and tracking. A decentralized controller with guaranteed exponential convergence is devised. The SCAT algorithm is verified in simulations and on a team of robots.

Control of swarms based on Hydrodynamic models

We address the problem of pattern generation in obstacle-filled environments by a swarm of mobile robots. Decentralized controllers are devised by using the Smoothed Particle Hydrodynamics (SPH) method. The swarm is modelled as an incompressible fluid subjected to external forces. Actual robot issues such as finite size and nonholonomic constraints are also addressed. Collision avoidance guarantees are discussed. Finally, in the absence of obstacles, we prove for the first time stability and convergence of controllers based on the SPH.

Swarm Coordination Based on Smoothed Particle Hydrodynamics Technique

The focus of this study is on the design of feedback control laws for swarms of robots that are based on models from fluid dynamics. We apply an incompressible fluid model to solve a pattern generation task. Possible applications of an efficient solution to this task are surveillance and the cordoning off of hazardous areas. More specifically, we use the smoothed-particle hydrodynamics (SPH) technique to devise decentralized controllers that force the robots to behave in a similar manner to fluid particles. Our approach deals with static and dynamic obstacles. Considerations such as finite size and nonholonomic constraints are also addressed. In the absence of obstacles, we prove the stability and convergence of controllers that are based on the SPH method. Computer simulations and actual robot experiments are shown to validate the proposed approach.

Moving least square reproducing kernel method for electromagnetic field computation

This paper presents the meshless moving least square reproducing kernel method, originating from mechanics, which is applied for the first time to the solution of electromagnetic problems. Two-dimensional static problems are studied and simulation results show good agreement with analytical and other numerical solutions.

A Meshless Method for Electromagnetic Field Computation Based on the Multiquadric Technique

A meshless method for electromagnetic field computation is developed based on the multiquadric interpolation technique. A global approximation to the solution is built based only on the discretization of the domain in nodes and the differential equations describing the problem in the domain and its boundary. An attractive characteristic of the multiquadric solution is that it is continuous and it has infinitely continuous derivatives. This is particularly important to obtain field quantities in electromagnetic analysis. The method is also capable of dealing with physical discontinuities present at the interface between different materials. The formulation is presented in the Cartesian and polar coordinates, which can be extended to other systems. We applied the formulation in the analysis of an electrostatic micromotor and a microstrip. The results demonstrate good agreement with other numerical technique, showing the adequacy of the proposed methodology for electromagnetic analysis

Fluids in Electrostatic Fields: An Analogy for Multirobot Control

This paper addresses the problem of controlling a large group of robots in a 2-D pattern generation task. Different from previous methodologies, our approach can be used in generic static environments, where obstacles may appear. This approach is based on the analogy with the simulation of fluids in electrostatic fields. By means of a weak coupling between the smoothed particle hydrodynamics and the finite element method we derive a scalable solution where decentralized controllers are provided

The element-free Galerkin method in three-dimensional electromagnetic problems

The element-free Galerkin (EFG) meshless method is being widely used in problems where it is difficult to construct a good mesh or remeshing is needed. Although most of these problems include three-dimensional (3-D) domains, few works are found using the EFG in three dimensions in all areas, including electromagnetism. In this paper, we present the formulation and numerical results concerning EFG parameters in a 3-D electromagnetic problem

Robot navigation based on electrostatic field computation

This paper addresses the problem of mobile robot navigation using artificial potential fields. Many potential field based methodologies are found in the robotics literature, but most of them have problems with spurious local minima, which cause the robot to stop before reaching its target position. Although some free of local minima methodologies are found in the literature, none of them are easy to implement and generalize for complex shaped environments and robots. We propose a perfect analogy between electrostatic field computation and robot path planning. Thus, an easy solution to the problem, which is based on standard finite-element methods, can be applied with generic geometries and can even take into account the robots orientation. To demonstrate the elegance of the proposed methodology, several experimental results with actual mobile robots are included

A Meshless Local Petrov–Galerkin Method for Three-Dimensional Scalar Problems

In this paper, we apply a meshless method based on local boundary integral equations (LBIEs) to solve electromagnetic problems. The discretization process is carried out through the use of special basis functions that, unlike the Finite Element Method, are not confined to an element and do not require the support of an underlying mesh. The approach herein developed can be applied to general three-dimensional scalar boundary value problems arising in electromagnetism.