The proceedings contain 18 papers. The topics discussed include: dynamic multi-party computation forever for swarm and cloud computing and code obfuscation;local, self-organizing strategies for robotic formation probl...
ISBN:
(纸本)9783642282089
The proceedings contain 18 papers. The topics discussed include: dynamic multi-party computation forever for swarm and cloud computing and code obfuscation;local, self-organizing strategies for robotic formation problems;local approximation algorithms for the uncapacitated metric facility location problem in power-aware sensor networks;maximizing network lifetime on the line with adjustable sensing ranges;sensorfusion: from dependence analysis via matroid bases to online synthesis;neighbor discovery in a sensor network with directional antennae;evader interdiction and collateral damage;efficient algorithms for network localization using cores of underlying graphs;minimizing average interference through topology control;on barrier resilience of sensor networks;continuous monitoring in the dynamic sensor field model;and minimum-cost broadcast through varying-size neighborcast.
robotics systems usually comprise sophisticated sensor and actuator systems with no less complex control applications. These systems are subject to frequent modifications and extensions and have to adapt to their envi...
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robotics systems usually comprise sophisticated sensor and actuator systems with no less complex control applications. These systems are subject to frequent modifications and extensions and have to adapt to their environment. While automation systems are tailored to particular production processes, autonomous vehicles must adaptively switch their sensors and controllers depending on environmental conditions. However, when designing and implementing the process control system, traditional control theory focuses on the control problem at hand without having this variability in mind. Thus, the resulting models and implementation artefacts are monolithic, additionally complicating the real-time system design. In this paper, we present a modularisation approach for the design of robotics process controlsystems, which not only aims for variability at design-time but also for adaptivity at run-time. Our approach is based on a layered control architecture, which includes an explicit interface between the two domains involved: control engineering and computer science. Our architecture provides separation of concerns in terms of independent building blocks and data flows. For example, the replacement of a sensor no longer involves the tedious modification of downstream filters and controllers. Likewise, the error-prone mapping of high-level application behaviour to the process control system can be omitted. We validated our approach by the example of an autonomous vehicle use case. Our experimental results demonstrate ease of use and the capability to maintain quality of control on par with the original monolithic design.
Cyber-Physical systems have been widely employed in safety critical applications including intelligent highways, autonomous vehicles and roboticsystems. State estimation is crucial for Cyber-Physical systems because ...
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Cyber-Physical systems have been widely employed in safety critical applications including intelligent highways, autonomous vehicles and roboticsystems. State estimation is crucial for Cyber-Physical systems because control commands that are sent to physical systems depend on the estimated states. The particle filter is a good candidate for state estimation due to its applicability to nonlinear and/or non-Gaussian dynamic systems. However, classical particle filters are not robust against false data injection from sensors compromised by attackers. In this paper, we propose a novel particle filter algorithm, trust aware particle filter, that is robust to false data injection attacks. We develop a framework in which a state estimator assigns trust values to sensors based on the measurements and we utilize the trust values in the state estimation. Simulation results demonstrate the robustness of the trust aware particle filter in the presence of false data injection attacks.
In this paper we propose a framework for semi-autonomous operation of an under-actuated underwater vehicle. The contributions of this paper are twofold: The first contribution is a visual servoing control scheme that ...
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In this paper we propose a framework for semi-autonomous operation of an under-actuated underwater vehicle. The contributions of this paper are twofold: The first contribution is a visual servoing control scheme that is designed to provide a human operator the capability to steer the vehicle without loosing the target from the vision system's field of view. It is shown that the under-actuated degree of freedom is input-to-state stable (ISS) and a shaping of the user input with stability guarantees is implemented. The resulting control scheme has formally guaranteed stability and convergence properties. The second contribution is an asynchronous Modified Dual Unscented Kalman Filter (MDUKF) for the on-line state and parameter estimation of the vehicle by fusing data from a Laser Vision System (LVS) and an Inertial Measurement Unit (IMU). The MDUKF has been developed in order to experimentally verify the performance of the proposed visual servoing control scheme. Experimental results of the visual servoing control scheme integrated with the asynchronous MDUKF indicate the feasibility and applicability of the proposed con-trol scheme. Experiments have been carried out on a small under-actuated Remotely Operated Vehicle (ROV) in a test tank.
A widely applied strategy for workload sharing is to equalize the workload assigned to each resource. In mobile multiagent systems, this principle directly leads to equitable partitioning policies whereby: 1) the envi...
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A widely applied strategy for workload sharing is to equalize the workload assigned to each resource. In mobile multiagent systems, this principle directly leads to equitable partitioning policies whereby: 1) the environment is equitably divided into subregions of equal measure;2) one agent is assigned to each subregion;and 3) each agent is responsible for service requests originating within its own subregion. The current lack of distributed algorithms for the computation of equitable partitions limits the applicability of equitable partitioning policies to limited-size multiagent systems operating in known, static environments. In this paper, first we design provably correct and spatially distributed algorithms that allow a team of agents to compute a convex and equitable partition of a convex environment. Second, we discuss how these algorithms can be extended so that a team of agents can compute, in a spatially distributed fashion, convex and equitable partitions with additional features, e.g., equitable and median Voronoi diagrams. Finally, we discuss two application domains for our algorithms, namely dynamic vehicle routing for mobile robotic networks and wireless ad hoc networks. Through these examples, we show how one can couple the algorithms presented in this paper with equitable partitioning policies to make these amenable to distributed implementation. More in general, we illustrate a systematic approach to devise spatially distributed control policies for a large variety of multiagent coordination problems. Our approach is related to the classic Lloyd algorithm and exploits the unique features of power diagrams.
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.
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.
autonomous vehicles are very hot research area which advance artificial intelligent, pattern recognition, computer vision, sensorfusion and control theory. In the paper we demonstrate a kind of micro-autonomous vehic...
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ISBN:
(纸本)9780769543499
autonomous vehicles are very hot research area which advance artificial intelligent, pattern recognition, computer vision, sensorfusion and control theory. In the paper we demonstrate a kind of micro-autonomous vehicle, describing hardware and software architectures, perception system and control method-cloud control. Our goal is study interaction behaviors between autonomous vehicles and how to take appropriate measure to avoid driving conditions hazardous. We propose a new control alogrithm-cloud control algorithm and experiments show cloud control algorithm has good performance and flexibility.
This paper presents a hardware system architecture for a mobile robotic system that employs multiple sensors (an ultrasonic array, a thermal sensor, and a video streaming system) to obtain information about the enviro...
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ISBN:
(纸本)9781880843833
This paper presents a hardware system architecture for a mobile robotic system that employs multiple sensors (an ultrasonic array, a thermal sensor, and a video streaming system) to obtain information about the environment, a virtual field strategy for obstacle avoidance and path planning, and an ANFIS controller for path tracking. The particular focus is on the ANFIS controller and its hardware implementation, the graphics-user interface and the overall system architecture. Experimental results and preliminary evaluation show that the proposed architecture is a feasible one for autonomous mobile roboticsystems.
In robotic contour following tasks such as sewing or cutting an industrial robot guides a tool along a contour of a workpiece. Teaching the task manually is very time consuming and the process would be unable to react...
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