1,732 research outputs found

    Experimental Testbed for Large Multirobot Teams

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    Experimental validation is particularly important in multirobot systems research. The differences between models and real-world conditions that may not be apparent in single robot experiments are amplified because of the large number of robots, interactions between robots, and the effects of asynchronous and distributed control, sensing, and actuation. Over the last two years, we have developed an experimental testbed to support research in multirobot systems with the goal of making it easy for users to model, design, benchmark, and validate algorithms. In this article, we describe our approach to the design of a large-scale multirobot system for the experimental verification and validation of a variety of distributed robotic applications in an indoor environment

    Object Manipulation using a Multirobot Cluster with Force Sensing

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    This research explored object manipulation using multiple robots by developing a control system utilizing force sensing. Multirobot solutions provide advantages of redundancy, greater coverage, fault-tolerance, distributed sensing and actuation, and reconfigurability. In object manipulation, a variety of solutions have been explored with different robot types and numbers, control strategies, sensors, etc. This research involved the integration of force sensing with a centralized position control method of two robots (cluster control) and building it into an object level controller. This controller commands the robots to push the object based on the measured interaction forces between them while maintaining proper formation with respect to each other and the object. To test this controller, force sensor plates were attached to the front of the Pioneer 3-AT robots. The object is a long, thin, rectangular prism made of cardboard, filled with paper for weight. An Ultra Wideband system was used to track the positions and headings of the robots and object. Force sensing was integrated into the position cluster controller by decoupling robot commands, derived from position and force control loops. The result was a successful pair of experiments demonstrating controlled transportation of the object, validating the control architecture. The robots pushed the object to follow linear and circular trajectories. This research is an initial step toward a hybrid force/position control architecture with cluster control for object transportation by a multirobot system

    A Software Suite for the Control and the Monitoring of Adaptive Robotic Ecologies

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    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

    A macroscopic analytical model of collaboration in distributed robotic systems

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    In this article, we present a macroscopic analytical model of collaboration in a group of reactive robots. The model consists of a series of coupled differential equations that describe the dynamics of group behavior. After presenting the general model, we analyze in detail a case study of collaboration, the stick-pulling experiment, studied experimentally and in simulation by Ijspeert et al. [Autonomous Robots, 11, 149-171]. The robots' task is to pull sticks out of their holes, and it can be successfully achieved only through the collaboration of two robots. There is no explicit communication or coordination between the robots. Unlike microscopic simulations (sensor-based or using a probabilistic numerical model), in which computational time scales with the robot group size, the macroscopic model is computationally efficient, because its solutions are independent of robot group size. Analysis reproduces several qualitative conclusions of Ijspeert et al.: namely, the different dynamical regimes for different values of the ratio of robots to sticks, the existence of optimal control parameters that maximize system performance as a function of group size, and the transition from superlinear to sublinear performance as the number of robots is increased

    Effects of alarms on control of robot teams

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    Annunciator driven supervisory control (ADSC) is a widely used technique for directing human attention to control systems otherwise beyond their capabilities. ADSC requires associating abnormal parameter values with alarms in such a way that operator attention can be directed toward the involved subsystems or conditions. This is hard to achieve in multirobot control because it is difficult to distinguish abnormal conditions for states of a robot team. For largely independent tasks such as foraging, however, self-reflection can serve as a basis for alerting the operator to abnormalities of individual robots. While the search for targets remains unalarmed the resulting system approximates ADSC. The described experiment compares a control condition in which operators perform a multirobot urban search and rescue (USAR) task without alarms with ADSC (freely annunciated) and with a decision aid that limits operator workload by showing only the top alarm. No differences were found in area searched or victims found, however, operators in the freely annunciated condition were faster in detecting both the annunciated failures and victims entering their cameras' fields of view. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved

    An Experimental Platform for Multi-spacecraft Phase-Array Communications

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    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

    Safe, Remote-Access Swarm Robotics Research on the Robotarium

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    This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference
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