1,431 research outputs found
Effects of spatial ability on multi-robot control tasks
Working with large teams of robots is a very complex and demanding task for any operator and individual differences in spatial ability could significantly affect that performance. In the present study, we examine data from two earlier experiments to investigate the effects of ability for perspective-taking on performance at an urban search and rescue (USAR) task using a realistic simulation and alternate displays. We evaluated the participants' spatial ability using a standard measure of spatial orientation and examined the divergence of performance in accuracy and speed in locating victims, and perceived workload. Our findings show operators with higher spatial ability experienced less workload and marked victims more precisely. An interaction was found for the experimental image queue display for which participants with low spatial ability improved significantly in their accuracy in marking victims over the traditional streaming video display. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved
An Experimental Platform for Multi-spacecraft Phase-Array Communications
The emergence of small satellites and CubeSats for interplanetary exploration
will mean hundreds if not thousands of spacecraft exploring every corner of the
solar-system. Current methods for communication and tracking of deep space
probes use ground based systems such as the Deep Space Network (DSN). However,
the increased communication demand will require radically new methods to ease
communication congestion. Networks of communication relay satellites located at
strategic locations such as geostationary orbit and Lagrange points are
potential solutions. Instead of one large communication relay satellite, we
could have scores of small satellites that utilize phase arrays to effectively
operate as one large satellite. Excess payload capacity on rockets can be used
to warehouse more small satellites in the communication network. The advantage
of this network is that even if one or a few of the satellites are damaged or
destroyed, the network still operates but with degraded performance. The
satellite network would operate in a distributed architecture and some
satellites maybe dynamically repurposed to split and communicate with multiple
targets at once. The potential for this alternate communication architecture is
significant, but this requires development of satellite formation flying and
networking technologies. Our research has found neural-network control
approaches such as the Artificial Neural Tissue can be effectively used to
control multirobot/multi-spacecraft systems and can produce human competitive
controllers. We have been developing a laboratory experiment platform called
Athena to develop critical spacecraft control algorithms and cognitive
communication methods. We briefly report on the development of the platform and
our plans to gain insight into communication phase arrays for space.Comment: 4 pages, 10 figures, IEEE Cognitive Communications for Aerospace
Applications Worksho
A Software Suite for the Control and the Monitoring of Adaptive Robotic Ecologies
Adaptive robotic ecologies are networks of heterogeneous robotic devices (sensors, actuators, automated appliances) pervasively embedded in everyday environments, where they learn to cooperate towards the achievement of complex tasks. While their flexibility makes them an increasingly popular way to improve a system’s reliability, scalability, robustness and autonomy, their effective realisation demands integrated control and software solutions for the specification, integration and management of their highly heterogeneous and computational constrained components. In this extended abstract we briefly illustrate the characteristic requirements dictated by robotic ecologies, discuss our experience in developing adaptive robotic ecologies, and provide an overview of the specific solutions developed as part of the EU FP7 RUBICON Project
Experiments in cooperative human multi-robot navigation
In this paper, we consider the problem of a
group of autonomous mobile robots and a human moving
coordinately in a real-world implementation. The group
moves throughout a dynamic and unstructured environment.
The key problem to be solved is the inclusion of a human in a
real multi-robot system and consequently the multiple robot
motion coordination. We present a set of performance metrics
(system efficiency and percentage of time in formation) and a
novel flexible formation definition whereby a formation
control strategy both in simulation and in real-world
experiments of a human multi-robot system is presented. The
formation control proposed is stable and effective by means of
its uniform dispersion, cohesion and flexibility
Coordinated Robot Navigation via Hierarchical Clustering
We introduce the use of hierarchical clustering for relaxed, deterministic
coordination and control of multiple robots. Traditionally an unsupervised
learning method, hierarchical clustering offers a formalism for identifying and
representing spatially cohesive and segregated robot groups at different
resolutions by relating the continuous space of configurations to the
combinatorial space of trees. We formalize and exploit this relation,
developing computationally effective reactive algorithms for navigating through
the combinatorial space in concert with geometric realizations for a particular
choice of hierarchical clustering method. These constructions yield
computationally effective vector field planners for both hierarchically
invariant as well as transitional navigation in the configuration space. We
apply these methods to the centralized coordination and control of
perfectly sensed and actuated Euclidean spheres in a -dimensional ambient
space (for arbitrary and ). Given a desired configuration supporting a
desired hierarchy, we construct a hybrid controller which is quadratic in
and algebraic in and prove that its execution brings all but a measure zero
set of initial configurations to the desired goal with the guarantee of no
collisions along the way.Comment: 29 pages, 13 figures, 8 tables, extended version of a paper in
preparation for submission to a journa
Dynamic Control of Mobile Multirobot Systems: The Cluster Space Formulation
The formation control technique called cluster space control promotes simplified specification and monitoring of the motion of mobile multirobot systems of limited size. Previous paper has established the conceptual foundation of this approach and has experimentally verified and validated its use for various systems implementing kinematic controllers. In this paper, we briefly review the definition of the cluster space framework and introduce a new cluster space dynamic model. This model represents the dynamics of the formation as a whole as a function of the dynamics of the member robots. Given this model, generalized cluster space forces can be applied to the formation, and a Jacobian transpose controller can be implemented to transform cluster space compensation forces into robot-level forces to be applied to the robots in the formation. Then, a nonlinear model-based partition controller is proposed. This controller cancels out the formation dynamics and effectively decouples the cluster space variables. Computer simulations and experimental results using three autonomous surface vessels and four land rovers show the effectiveness of the approach. Finally, sensitivity to errors in the estimation of cluster model parameters is analyzed.Fil: Mas, Ignacio Agustin. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones CientÃficas y Técnicas; ArgentinaFil: Kitts, Christopher. Santa Clara University; Estados Unido
Coordination of Multirobot Teams and Groups in Constrained Environments: Models, Abstractions, and Control Policies
Robots can augment and even replace humans in dangerous environments, such as search and rescue and reconnaissance missions, yet robots used in these situations are largely tele-operated. In most cases, the robots\u27 performance depends on the operator\u27s ability to control and coordinate the robots, resulting in increased response time and poor situational awareness, and hindering multirobot cooperation.
Many factors impede extended autonomy in these situations, including the unique nature of individual tasks, the number of robots needed, the complexity of coordinating heterogeneous robot teams, and the need to operate safely. These factors can be partly addressed by having many inexpensive robots and by control policies that provide guarantees on convergence and safety.
In this thesis, we address the problem of synthesizing control policies for navigating teams of robots in constrained environments while providing guarantees on convergence and safety. The approach is as follows. We first model the configuration space of the group (a space in which the robots cannot violate the constraints) as a set of polytopes. For a group with a common goal configuration, we reduce complexity by constructing a configuration space for an abstracted group state. We then construct a discrete representation of the configuration space, on which we search for a path to the goal. Based on this path, we synthesize feedback controllers, decentralized affine controllers for kinematic systems and nonlinear feedback controllers for dynamical systems, on the polytopes, sequentially composing controllers to drive the system to the goal. We demonstrate the use of this method in urban environments and on groups of dynamical systems such as quadrotors.
We reduce the complexity of multirobot coordination by using an informed graph search to simultaneously build the configuration space and find a path in its discrete representation to the goal. Furthermore, by using an abstraction on groups of robots we dissociate complexity from the number of robots in the group. Although the controllers are designed for navigation in known environments, they are indeed more versatile, as we demonstrate in a concluding simulation of six robots in a partially unknown environment with evolving communication links, object manipulation, and stigmergic interactions
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