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检索条件"机构=Robotics Embedded Systems Laboratory Robotics Research Laboratory Department of Computer Science"

共 484 条记录，以下是381-390 订阅

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Modular hybrid Petri nets for studying multi-operational production systems where parts follow multiple alternative processes

Modular hybrid Petri nets for studying multi-operational pro...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： G.J. Tsinarakis K.P. Valavanis Intelligent Systems and Robotics Laboratory Department of Production Engineering and Management Technical University of Crete Chania Greece Department of Computer Science and Engineering University of South Florida Center for Robot-Assisted Search and Rescue Tampa FL USA

This work presents a modular hybrid timed Petri net (MHTPN) methodology used to study multi-operational production systems in which parts are used for the production of different product types. This research generalizes work presented in Tsinarakis, GJ et al., (2003) that studied production systems where all parts of the same type were used for the production of a type of final products following a common route. 3 fundamental system modules are derived; their MHTPN models are defined, followed by modules synthesis to obtain the overall system Petri net. For any topology, system's nodes and invariants are calculated. Applicability of the method is illustrated through an analytical example.

关键词： Petri nets Production systems Topology Fluid dynamics Assembly Intelligent robots Hybrid intelligent systems Laboratories Production engineering Engineering management

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Panel: given that hardware verification has been an uphill battle, what is the future of software verification?

Panel: given that hardware verification has been an uphill b...

引用

ACM and IEEE International Conference on Formal Methods and Models for Co-Design (MEMOCODE)

作者： S.K. Shukla T. Bultan C. Heitmeyer FERMAT Laboratory Center for Embedded Systems for Critical Applications Virginia Technology Blacksburg VA USA Department of Computer Science University of California슠Santa Barbara Santa Barbara CA USA Naval Research Laboratory Inc. Washington D.C. USA

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Multi-robot task-allocation through vacancy chains

Multi-robot task-allocation through vacancy chains

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IEEE International Conference on robotics and Automation (ICRA)

作者： T.S. Dahl M.J. Mataric G.S. Sukhatme Robotics Research Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California USA

This paper presents an algorithm for task allocation in groups of homogeneous robots. The algorithm is based on vacancy chains, a resource distribution strategy common in human and animal societies. We define a class of task-allocation problems for which the vacancy chain algorithm is suitable and demonstrate how reinforcement learning can be used to make vacancy chains emerge in a group of behavior-based robots. Experiments in simulation show that the vacancy chain algorithm consistently outperforms random and static task allocation algorithms when individual robots are prone to distractions or breakdowns, or when task priorities change.

关键词： Scheduling algorithm Resource management Humans Learning Robot sensing systems Laboratories embedded system computer science Animals Electric breakdown

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Putting the 'I' in 'Team': An ego-centric approach to cooperative localization

Putting the 'I' in 'Team': An ego-centric approach to cooper...

引用

2003 IEEE International Conference on robotics and Automation

作者： Howard, Andrew Matarić, Maja J. Sukhatme, Gaurav S. Robotics Research Laboratory Computer Science Department University of Southern California Los Angeles CA 90089-0781 United States

This paper describes a cooperative method for relative localization of mobile robot teams;that is, it describes a method whereby every robot in the team can estimate the pose of every other robot, relative to itself. This method does not require the use GPS, landmarks, or maps of any kind;instead, robots make direct measurements of the relative pose of nearby robots, and broadcast this information to the team as a whole. Each robot processes this information independently to generate an ego-centric estimate for the pose of other robots. Our method uses a Bayesian formalism with a particle filter implementation, and is, as a consequence, very robust. It is also completely distributed, yet requires relatively little communication between robots. This paper describes the basic ego-centric formalism, sketches the implementation, and presents experimental results obtained using a team of four mobile robots.

关键词： computer vision

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Towards Stealthy Behaviors

Towards Stealthy Behaviors

引用

2003 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Birgersson, Emil Howard, Andrew Sukhatme, Gaurav S. Robotics Research Laboratory Computer Science Department University of Southern California Los Angeles CA 90089-0781 United States

This paper describes a behavior-based approach to stealth. The specific problem we consider is that of making stealthy traverses, i.e., transiting from one point to another while remaining hidden from an observer. Since we assume that the robot has no a priori model of the environment, our stealthy traverse behavior makes opportunistic use of terrain features to hide from the observer. This behavior has been evaluated in both real and simulated experiments, comparing it against a regular goal-seeking/obstacle-avoidance behavior. These experiments show a clear improvement in the stealthiness of the robot.

关键词： Intelligent robots

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Sensor network-based multi-robot task allocation

Sensor network-based multi-robot task allocation

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： M.A. Batalin G.S. Sukhatme Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Computer Science Department University of Southern California Los Angeles CA USA

We present DINTA, distributed in-network task allocation - a novel paradigm for multi-robot task allocation (MRTA) where tasks are allocated implicitly to robots by a pre-deployed, static sensor network. Experimental results with a simulated alarm scenario show that our approach is able to compute solutions to the MRTA problem in a distributed fashion. We compared our approach to a strategy where robots use the deployed sensor network for efficient exploration. The data show that our approach outperforms such an exploration-only algorithm. The data also provide evidence that the proposed algorithm is more stable than the exploration-only algorithm.

关键词： Robot sensing systems Navigation computer networks Distributed computing embedded system Mobile robots Laboratories computer science Sensor systems Computational modeling

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Efficient exploration without localization

Efficient exploration without localization

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IEEE International Conference on robotics and Automation (ICRA)

作者： M.A. Batalin G.S. Sukhatme Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Computer Science Department University of Southern California Los Angeles CA USA Center for Robotics and Embedded Systems University of Southern California Los Angeles CA USA

We study the problem of exploring an unknown environment using a single robot. The environment is large enough (and possibly dynamic) that constant motion by the robot is needed to cover the environment. We term this the dynamic coverage problem. We present an efficient minimalist algorithm which assumes that global information is not available to the robot (neither a map, nor GPS). Our algorithm uses markers which the robot drops off as signposts to aid exploration. We conjecture that our algorithm has a cover time better than O(n log n), where the n markers that are deployed form the vertices of a regular graph. We provide experimental evidence in support of this conjecture. We show empirically that the performance of our algorithm on graphs is similar to its performance in simulation.

关键词： Robot sensing systems embedded system Orbital robotics computer science Global Positioning System Target tracking Monitoring Security Buildings Earthquakes

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Human motion-based environment complexity measures for robotics

Human motion-based environment complexity measures for robot...

引用

IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： D.A. Shell M.J. Mataric Interaction Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California Los Angeles CA USA

This paper describes how environmental complexity measures can be employed in the process of validating experimental robotics work. We advocate the use of metrics that attempt to quantify the 'difficulty' of motion for a given environment. Space syntax methods (from the urban and building design literature) and fluid-flow models (used in crowd modeling) are described and proposed as relevant measures for mobile robotics domains. We show experimentally that these two metrics give very different expressions of complexity. We then discuss how, given their properties, these different metrics may be applied to robotics controller design and evaluation.

关键词： Humans Orbital robotics Motion measurement Mobile robots Robot sensing systems Time measurement Extraterrestrial measurements Robot vision systems embedded system computer science

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Putting the 'I' in 'team': an ego-centric approach to cooperative localization

Putting the 'I' in 'team': an ego-centric approach to cooper...

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IEEE International Conference on robotics and Automation (ICRA)

作者： A. Howard M.J. Mataric G.S. Sukhatme Robotics Research Laboratory Computer Science Department University of Southern California Los Angeles CA USA

This paper describes a cooperative method for relative localization of mobile robot teams; that is, it describes a method whereby every robot in the team can estimate the pose of every other robot, relative to itself. This robot does not require the use of GPS, landmarks, or maps of any kind; instead, robots make direct measurement of the relative pose of nearby robots, and broadcast this information to the team as a whole. Each robot processes this information independently to generate ego-centric estimate for the pose of other robots. Our method uses Bayesian formalism with a particle filter implementation, and is, as a consequence, very robust. It is also completely distributed, yet requires relatively little communication between robots. This paper describes the basic ego-centric formalism, sketches the implementation, and presents experimental results obtained using a team of four mobile robots.

关键词： Robot kinematics Robot sensing systems Mobile robots Broadcasting Global Positioning System Laboratories computer science Mobile computing Bayesian methods Particle filters

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Towards stealthy behaviors

Towards stealthy behaviors

引用

IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： E. Birgersson A. Howard G.S. Sukhatme Robotics Research Laboratory Computer Science Department University of Southern California Los Angeles CA USA

关键词： Observability Orbital robotics Robot sensing systems Object detection Laboratories computer science Ray tracing Robot control Global Positioning System Simultaneous localization and mapping

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