The objective of this research is to develop decentralized methods for achieving robustness in multi-agent networks through self-organization. Multi-agent networks typically consist of numerous components that interact with each other to achieve some collaborative tasks. In many applications, the network may face functional or structural challenges such as failures, noise, or malicious attacks, to name a few. Under such perturbations, a desirable […]
We approach the problem of having robots mix, or interact with each other consistently in the same space, by borrowing concepts from algebraic topology, namely from the Braid Group.
Sim.I.am is a mobile robot simulator designed to allow students to bridge the gap between theory and practice in control theory. It enables students to design controllers for a mobile robot, test these controllers in a simulator, and then deploy these controllers on an actual robotic platform: the Khepera III mobile robot (and others). This […]
What is the minimum amount of information required by a team of networked agents to solve a geometric task? This notion of minimality is explored through the use of set-valued sensors, and the question then becomes what assumptions need to be made on these sensor models. In fact, the set-valued sensor provides a general model […]
In this project, optimal coverage ideas are used to control a multi-agent system. In optimal coverage, we are concerned with finding the algorithm that will drive the agents to position themselves in ‘best’ locations, when given a certain density function that represents spatial ‘importance’. For example, this density function may be a probability density function of […]
As the trends towards decentralization, miniaturization, and longevity of deployment continue in many domains, power management has become increasingly important. In sensing and communications networks, power management has long been a part of the design paradigm. However, an underlying assumption in most of the existing work is that the performance of the sensing devices remain […]
This project develops a novel approach for heterogeneous self-reconfiguration of a modular robot comprised of heterogeneous cubic modules. We allow an arbitrary number of modules and module classes and show that the proposed self-reconfiguration algorithm can guarantee completion of heterogeneous self-reconfiguration sequences by avoiding so-called hole obstructions. We introduce a hole-detection algorithm to avoid creating […]
In networked systems, a designer often has a higher level goal in mind which he wants to achieve with local rules. Examples of possible goals are rendezvous and formation control. This project aims to find general methods by which arbitrary global behaviors can be mapped on to local network interactions. Initial work has shown that […]
In the case of leader-follower networks, one or more agents (the leaders) can be used to inject control inputs into the system. In these networks, one can analyze the “effectiveness” of the inputs by borrowing a notion from robotics known as manipulability. In robotics, manipulability indices were developed as a means to analyze the […]
Several Next Generation Air Transportation Systems concepts require aircraft to be able to safely fly routes on the same airspace in a timely fashion. Therefore it is necessary that aircraft are able to navigate on routes with spatial and temporal constraints. Here at the GRITS Lab, we propose an optimal control approach at solving the problem.
Many tasks to be solved by multi-agent systems can be formed in terms of a cost, where task completion corresponds to minimizing the cost. For example, the figure below depicts multi-agent formation control where agents must collectively decide upon parameters of the formation (such as displacement, rotation, and spread) while moving into position. By having […]
As robots evolve they are becoming increasingly “smarter”, but still can not and do not learn the way humans learn. For example, humans have evolved to move by walking or running; however, humans can learn how to move by other means (e.g. swimming, skateboarding, riding bikes, etc.). I don’t know of any current robot that […]
The idea behind this project is to route multiple robots to service spatially distributed requests at specified time instants, while optimizing some criterion, for instance the total distance travelled, or the total time of travel. The routing problem is similar to the well known Multiple Traveling Salesman Problem (m-TSP) or the Vehicle Routing Problem (VRP), except […]
The goal of this project is to develop distributed control strategies to automatically reconfigure an ensemble of individual robotic modules from an initial configuration into a desired target configuration. A configuration in our work is a three-dimensional geometric arrangement of cubic modules where a cubic module is the basic building block of our system. Modular […]
The project is divided into three main research tasks: Puppet Choreography with Motion Programs, Imitating Human Motions, and Distributed Protocols for Coordinating Puppets.
The primary goal for this research is to develop a method of dynamic role assignment and formation control for multi-robot systems for rotationally and translationally invariant formations. Most previous work has treated assignment and formation synthesis as two separate problems.
The typical approach in the receding horizon framework is to choose a fixed time horizon over which to predict the unknown variables and obtain the optimal control input. If we had perfect estimates we could then make the time horizon as large as possible subject to factors such as computation speed, convergence, stability, and satisfaction […]
Stylistic Task Specification Framework applied to Aldebaran NAO robotic platform Typically, robotic algorithms focus on tasks which have concrete, functional objectives. Our framework aims to allow for more general specification based on stylistic considerations. Namely, we may think of the movement styles exhibited by classical ballerinas, disco dancers, and cheerleaders as differentiated by distinct stylistic tasks. […]
Mobile Communication Networks Exploration of complex and dangerous territories posts great challenges for robotics research. Intuition suggests that using cooperative multiple vehicles will increase time efficiency. Coordination of multiple vehicles typically relies on communication between vehicles, but direct communication is easily blocked or at least attenuated by obstacles. Hence one major challenge for a successful […]
Biologically Inspired Heterogeneous Networks Social behavior of animals can offer solution models for missions involving a large number of heterogeneous vehicles, such as light combat ships, unmanned aerial vehicles, and unmanned underwater vehicles. We draw inspiration from the bottlenose dolphins, Tursiops truncatus, and develop coordination algorithms for heterogeneous multi-agent systems that are expressive enough to […]