This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha-beta coordination strategy is a family of collect...
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This paper presents an analysis of a decentralized coordination strategy for organizing and controlling a team of mobile robots performing collective search. The alpha-beta coordination strategy is a family of collective search algorithms that allow teams of communicating robots to implicitly coordinate their search activities through a division of labor based on self-selected roles. In an alpha-beta team, alpha agents are motivated to improve their status by exploring new regions of the search space. Beta agents are conservative, and rely on the alpha agents to provide advanced information on favorable regions of the search space. An agent selects its current role dynamically based on its current status value relative to the current status values of the other team members. Status is determined by some function of the agent's sensor readings, and is generally a measurement of source intensity at the agent's current location. Variations on the decision rules determining alpha and beta behavior produce different versions of the algorithm that lead to different global properties. The alpha-beta strategy is based on a simple finite-state machine that implements a form of Variable Structure control (VSC). The VSC system changes the dynamics of the collective system by abruptly switching at defined states to alternative control laws. In VSC, Lyapunov's direct method is often used to design control surfaces which guide the system to a given goal. We introduce the alpha-beta algorithm and present an analysis of the equilibrium point and the global stability of the alpha-beta algorithm based on Lyapunov's method.
The Accident Response Mobile Manipulator System (ARMMS) is a teleoperated emergency response vehicle that deploys two hydraulic manipulators, five cameras, and an array of sensors to the scene of an incident. It is op...
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The Accident Response Mobile Manipulator System (ARMMS) is a teleoperated emergency response vehicle that deploys two hydraulic manipulators, five cameras, and an array of sensors to the scene of an incident. It is operated from a remote base station that can be situated up to four kilometers away from the site. Recently, a modular telerobot control architecture called SMART (Sandia's Modular Architecture for robotic and Teleoperation) was applied to ARMMS to improve the precision, safety, and operability of the manipulators on board. Using SMART, a prototype manipulator control system was developed in a couple of days, and an integrated working system was demonstrated within a couple of months. New capabilities such as camera-frame teleoperation, autonomous tool changeout and dual manipulator control have been incorporated. The final system incorporates twenty-two seperate modules and implements seven different behavior modes. This paper describes the integration of SMART into the ARMMS system.
In this paper, a model-free data fusion method for combining redundant sensor data is presented. The objective is to maintain a reliable tool center point pose measurement of a long-reach robotic manipulator using a v...
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ISBN:
(纸本)9788993215243
In this paper, a model-free data fusion method for combining redundant sensor data is presented. The objective is to maintain a reliable tool center point pose measurement of a long-reach robotic manipulator using a visual sensor system with multiple cameras. The fusion method is based on weighted averaging. The weight parameter for each variable is computed using the sliding window variance with N latest observations. After each sliding window, the window length N is updated, and simple transition smoothing is included. For experimental validation, two sets of pose trajectory data from redundant visual sensors were obtained: 1) using a camera located near the tip of a long-reach manipulator running a simultaneous localization and mapping (SLAM) algorithm and 2) marker-based tracking with cameras located near the base of the manipulator. For pose tracking, a fiducial marker was attached near the SLAM camera. The proposed methodology was examined using a real-time measurement setup and offline data analysis using the recorded data. The results demonstrate that the proposed system can increase the overall robustness and fault tolerance of the system, which are desired features for future autonomous field robotic machines.
Commercially successful autonomous mobile robot systems demand the development of new methodologies for dealing with 'real world' requirements of very low cost and very high performance sensing technology for ...
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ISBN:
(纸本)0780319338
Commercially successful autonomous mobile robot systems demand the development of new methodologies for dealing with 'real world' requirements of very low cost and very high performance sensing technology for use in the constantly changing, dynamic, unstructured environments in which society expects such robots to operate unsupervised on a daily basis. This paper presents a new modular sensor system which, based on long term real world field trials appear to meet the basic requirements. Examples of test results in a wide variety of applications in unstructured environments are provided as well as future directions.
The paper presents a novel approach toward modeling and governing complex system behavior in flexible and adaptive robotic assembly systems. A fully distributed multiagent approach is implemented for autonomous contro...
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The paper presents a novel approach toward modeling and governing complex system behavior in flexible and adaptive robotic assembly systems. A fully distributed multiagent approach is implemented for autonomouscontrol. The system is defined at multiple levels of granularity where agents provide services in respect to the current global goal. A decentralized multiagent approach is adopted for reasons of flexibility and fault tolerance embedded in the design phase. To prove the concept a robotic application for intelligent assembly is presented and discussed. It consists of multiple industrial robots equipped with force/torque sensors, 2D and 3D vision systems, automatic tool changers and other sensors and actuators. Through fusion of sensory input and mutual communication agents construct and negotiate an assembly plan and reconfigure respectively. (C) 2011 Published by Elsevier B. V.
The accuracy of sensorfusion algorithms are limited by either the intrinsic sensor noise, or by the quality of time synchronization of the sensors. While the intrinsic sensor noise only depends on the respective sens...
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ISBN:
(数字)9781665473385
ISBN:
(纸本)9781665473385
The accuracy of sensorfusion algorithms are limited by either the intrinsic sensor noise, or by the quality of time synchronization of the sensors. While the intrinsic sensor noise only depends on the respective sensors, the error induced by quality of, or lack of, synchronization depends on the dynamics of the vehicles and robotic system and the magnitude of time synchronization errors. To meet their sensorfusion requirements, system designers must consider both which sensor to use and also how to synchronize them. This paper presents the Syncline model, a simple visual model of how time synchronization affects the accuracy of sensorfusion for different mobile robot platform. The model can serve as a simple tool to determine which synchronization mechanisms should be used.
roboticsensor networks (RSNs), which consist of networks of sensors placed on mobile robots, are being increasingly used for environment monitoring applications. In particular, a lot of work has been done on simultan...
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ISBN:
(纸本)9781628410532
roboticsensor networks (RSNs), which consist of networks of sensors placed on mobile robots, are being increasingly used for environment monitoring applications. In particular, a lot of work has been done on simultaneous localization and mapping of the robots, and optimal sensor placement for environment state estimation(1). The deployment of RSNs, however, remains challenging in harsh environments where the RSNs have to deal with significant perturbations in the forms of wind gusts, turbulent water flows, sand storms, or blizzards that disrupt inter-robot communication and individual robot stability. Hence, there is a need to be able to control such perturbations and bring the networks to desirable states with stable nodes (robots) and minimal operational performance (environment sensing). Recent work has demonstrated the feasibility of controlling the non-linear dynamics in other communication networks like emergency management systems and power grids by introducing compensatory perturbations to restore network stability and operation(2). In this paper, we develop a computational framework to investigate the usefulness of this approach for RSNs in marine environments. Preliminary analysis shows promising performance and identifies bounds on the original perturbations within which it is possible to control the networks.
In order to perform sensor-based map building of in-door environment for autonomous mobile robot, this paper presents a methodology allowing the merging of degrees of confidence associated to believes represented by b...
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ISBN:
(纸本)0780332148
In order to perform sensor-based map building of in-door environment for autonomous mobile robot, this paper presents a methodology allowing the merging of degrees of confidence associated to believes represented by binary propositions. Such a belief is, by hypothesis, the member ship of a element to a given set. Degree of confidence notion is introduced in the combined framework of logic and probability theory. The problem is posed as follows: if different experts give their own degrees of confidence in a belief H, how is if possible to merge these degrees? This paper develops only the case in which experts characterize different elements belonging to the same set Obtained results are applied to ultrasonic range data fusion.
This paper proposes and evaluates a framework for cooperative control of a multi-agent system. The framework is evaluated on a target-tracking application where a distributed sensor network is tasked to autonomously o...
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This paper proposes and evaluates a framework for cooperative control of a multi-agent system. The framework is evaluated on a target-tracking application where a distributed sensor network is tasked to autonomously observe targets within the environment. The problem of cooperative control is defined using two distinct levels of cooperation: implicit and explicit. Implicit cooperation is defined as cooperation through only the exchange of environmental data to compile a common picture over which to reason locally. For example, in this paper, decentralized data fusion algorithms are used to build and update a common picture of the target positions and velocities. Explicit cooperation, which is the main focus of this paper, negotiates the agents explicitly on a joint set of actions to perform. In this paper, the problem of explicit cooperation is formulated as a distributed optimization, and a framework to find the joint set of actions is proposed. The framework utilizes two algorithms, the Max-Sum algorithm, to globally solve a factorizable utility function, and Probability Collectives (PC), to solve the individual factors of the utility function. The paper presents experimental results of the two algorithms using a simulated distributed sensor network when the tracking problem is and is not factorizable. The results show that the proposed framework can efficiently and effectively enable cooperation in a distributed sensor network. The Max-Sum algorithm provides a distributed and flexible approach to solve a factorizable utility function, where the PC algorithm was shown to efficiently solve the individual factors when more than four sensors are required to cooperate.
This paper develops active Simultaneous Localisation And Mapping (SLAM) trajectory control strategies for multiple cooperating Unmanned Aerial Vehicles (UAVs) for tasks such as surveillance and picture compilation in ...
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This paper develops active Simultaneous Localisation And Mapping (SLAM) trajectory control strategies for multiple cooperating Unmanned Aerial Vehicles (UAVs) for tasks such as surveillance and picture compilation in Global Positioning System (GPS)-denied environments. Each UAV in the team uses inertial sensor and terrain sensor information to simultaneously localise the UAV while building a point feature map of the surrounding terrain, where map information is shared between vehicles over a data fusion network. Multi-vehicle active SLAM control architectures are proposed that actively plan the trajectories and motions of each of the vehicles in the team based on maximising information in the localisation and mapping estimates. We demonstrate and compare an ideal, centralised architecture, where a central planning node chooses optimal actions for each UAV, and a coordinated, decentralised architecture, where UAVs make their own control decisions based on common shared map information. The different architectures involve varying degrees of complexity and optimality through differing communications and computational requirements. Results are presented using a three-UAV team in a six-degree of freedom multi-UAV simulator.
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