3,003 research outputs found
Progress toward multiârobot reconnaissance and the MAGIC 2010 competition
Tasks like searchâandârescue and urban reconnaissance benefit from large numbers of robots working together, but high levels of autonomy are needed to reduce operator requirements to practical levels. Reducing the reliance of such systems on human operators presents a number of technical challenges, including automatic task allocation, global state and map estimation, robot perception, path planning, communications, and humanârobot interfaces. This paper describes our 14ârobot team, which won the MAGIC 2010 competition. It was designed to perform urban reconnaissance missions. In the paper, we describe a variety of autonomous systems that require minimal human effort to control a large number of autonomously exploring robots. Maintaining a consistent global map, which is essential for autonomous planning and for giving humans situational awareness, required the development of fast loopâclosing, map optimization, and communications algorithms. Key to our approach was a decoupled centralized planning architecture that allowed individual robots to execute tasks myopically, but whose behavior was coordinated centrally. We will describe technical contributions throughout our system that played a significant role in its performance. We will also present results from our system both from the competition and from subsequent quantitative evaluations, pointing out areas in which the system performed well and where interesting research problems remain. © 2012 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93532/1/21426_ftp.pd
Concurrent Constrained Optimization of Unknown Rewards for Multi-Robot Task Allocation
Task allocation can enable effective coordination of multi-robot teams to
accomplish tasks that are intractable for individual robots. However, existing
approaches to task allocation often assume that task requirements or reward
functions are known and explicitly specified by the user. In this work, we
consider the challenge of forming effective coalitions for a given
heterogeneous multi-robot team when task reward functions are unknown. To this
end, we first formulate a new class of problems, dubbed COncurrent Constrained
Online optimization of Allocation (COCOA). The COCOA problem requires online
optimization of coalitions such that the unknown rewards of all the tasks are
simultaneously maximized using a given multi-robot team with constrained
resources. To address the COCOA problem, we introduce an online optimization
algorithm, named Concurrent Multi-Task Adaptive Bandits (CMTAB), that leverages
and builds upon continuum-armed bandit algorithms. Experiments involving
detailed numerical simulations and a simulated emergency response task reveal
that CMTAB can effectively trade-off exploration and exploitation to
simultaneously and efficiently optimize the unknown task rewards while
respecting the team's resource constraints.Comment: 9 pages, 5 figures, to be published in RSS 202
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent âdevicesâ, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew âcognitive devicesâ are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Modelling and Verification of Multiple UAV Mission Using SMV
Model checking has been used to verify the correctness of digital circuits,
security protocols, communication protocols, as they can be modelled by means
of finite state transition model. However, modelling the behaviour of hybrid
systems like UAVs in a Kripke model is challenging. This work is aimed at
capturing the behaviour of an UAV performing cooperative search mission into a
Kripke model, so as to verify it against the temporal properties expressed in
Computation Tree Logic (CTL). SMV model checker is used for the purpose of
model checking
Towards adaptive multi-robot systems: self-organization and self-adaptation
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugÀnglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible
Human-robot teamwork: a knowledge-based solution
Dissertação apresentada na Faculdade de CiĂȘncias e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia ElectrotĂ©cnica e de ComputadoresTeams of humans and robots pose new challenges to the teamwork field. This stems from the fact that robots and humans have significantly different perceptual, reasoning, communication and actuation capabilities. This dissertation contributes to solving this problem by proposing a
knowledge-based multi-agent system to support design and execution of stereotyped (i.e. recurring) human-robot teamwork. The cooperative workflow formalism has been selected to specify team plans, and adapted to allow activities to share structured data, even during their execution.
This novel functionality enables tightly coupled interactions among team members.
Rather than focusing on automatic teamwork planning, this dissertation proposes a complementary and intuitive knowledge-based solution for fast deployment and adaptation of small scale human-robot teams.
In addition, the system has been designed in order to improve task awareness of each mission participant, and of the human overall mission awareness.
A set of empirical results obtained from simulated and real missions proved the concept and the reusability of such a system. Practical results showed that this approach used is an effective solution for small scale teams in stereotyped human-robot teamwork
Automation and robotics for the Space Exploration Initiative: Results from Project Outreach
A total of 52 submissions were received in the Automation and Robotics (A&R) area during Project Outreach. About half of the submissions (24) contained concepts that were judged to have high utility for the Space Exploration Initiative (SEI) and were analyzed further by the robotics panel. These 24 submissions are analyzed here. Three types of robots were proposed in the high scoring submissions: structured task robots (STRs), teleoperated robots (TORs), and surface exploration robots. Several advanced TOR control interface technologies were proposed in the submissions. Many A&R concepts or potential standards were presented or alluded to by the submitters, but few specific technologies or systems were suggested
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