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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Kaupp, Tobias Douillard, Bertrand Upcroft, Ben Makarenko, Alexei Univ Sydney ARC Ctr Excellence Autonomous Syst CAS Sydney NSW 2006 Australia

ISBN: (纸本)9781424402588

This paper considers the problem of building environment models by fusing information gathered by robotic platforms with human perceptual information. Rich environment models are required in real applications for both autonomous operation of robots and to support human decision-making. Hierarchical models are well suited to represent complex environments because they: offer multiple abstractions of the available information to support analysis and decision-making, and permit the incorporation of higher-level human observations. The contributions of this paper are two-fold: (1) development of a probabilistic three-level environment model for distributed information gathering, and (2) experimental demonstration of fully decentralized, cooperative human-robot information gathering using an outdoor sensor network comprised of an unmanned air vehicle, a ground vehicle, and two human operators. Several information exchange patterns are presented which qualitatively demonstrate human-robot information fusion.

关键词： information fusion human-robot teams hierarchical model sensor network

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A decentralized Cooperative Approach to Gentle Human Transportation with Mobile Robots Based on Tactile Feedback 1

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16th International Symposium on Distributed autonomous robotic systems (DARS)

作者： Zhang, Yi Sueoka, Yuichiro Ishihara, Hisashi Tsunoda, Yusuke Osuka, Koichi Osaka Univ Suita Osaka 5650871 Japan

ISBN: (数字)9783031514975

ISBN: (纸本)9783031537035;9783031514975;9783031514968

Cooperative transportation of objects by a group of small mobile robots is expected to work in disaster sites. In this study, we aim to transport fragile objects including humans which may move during the transport, with as little burden as possible. We propose the adoption of a flexible tri-axis tactile sensor with thickness at the top of the robot on which the object is mounted for safe support and state monitoring. We improved the leader-follower based control by adding force feedback into the leader's control law to prevent excessive force on the object, which is the disadvantage of the typical leader-follower method. We verified the robots can transport a rigid body gently with the proposed control law by converging their speeds to the same value in a dynamical simulation and actual experiments. Additionally, we found that multijoint objects also can be transported with the proposed method, whereas the stable support of the object by each robot is reserved for future works.

关键词： cooperative transportation flexible tactile sensor human transportation

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REAL WORLD APPLICATION OF A LOW-COST HIGH-PERFORMANCE sensor SYSTEM FOR autonomous MOBILE ROBOTS

REAL WORLD APPLICATION OF A LOW-COST HIGH-PERFORMANCE SENSOR...

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IEEE/RSJ/GI International Conference on Intelligent Robots and systems - Advanced robotic systems and the Real World

作者： BURHANPURKAR, VP CYBERWORKS INC ORILLIAON L3V 6H1CANADA

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.

关键词： INTELLIGENT MOTION control autonomous MOBILE ROBOTS sensorY fusion SERVICE ROBOTS NAVIGATION PATH PLANNING ULTRASONICS

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A Framework for Cooperative control Applied to a Distributed sensor Network

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COMPUTER JOURNAL 2011年第3期54卷 471-481页

作者： Waldock, Antony Nicholson, David BAE Syst Adv Technol Ctr Bristol Avon England

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.

关键词： cooperative control distributed sensor networks probability collectives Max-Sum

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Degrees of confidence fusion in a probabilistic context - Application to range data fusion

Degrees of confidence fusion in a probabilistic context - Ap...

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1996 IEEE/RSJ International Conference on Intelligent Robots and systems - robotic Intelligence Interacting with Dynamic Worlds (IROS 96)

作者： Piat, E Meizel, D CNRS Compiegne France

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.

关键词： sensor data fusion

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A Spatio-Temporal-Semantic Environment Representation for autonomous Mobile Robots equipped with various sensor systems

A Spatio-Temporal-Semantic Environment Representation for Au...

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IEEE International Conference on Multisensor fusion and Integration for Intelligent systems (MFI)

作者： Niemeyer, Mark Puetz, Sebastian Hertzberg, Joachim Plan Based Robot Control Grp German Res Ctr Artificial Intelligence Osnabruck Germany Osnabruck Univ Knowledge Based Syst Grp Osnabruck Germany Nat Robots GmbH Osnabruck Germany

ISBN: (数字)9781665460262

ISBN: (纸本)9781665460262

The large amount of high resolution sensor data, both temporal and spatial, that autonomous mobile robots collect in today's systems requires structured and efficient management and storage during the robot mission. In response, we present SEEREP: A Spatio-Temporal-Semantic Environment Representation for autonomous Mobile Robots. SEEREP handles various types of data at once and provides an efficient query interface for all three modalities that can be combined for high-level analyses. It supports common robotic sensor data types such as images and point clouds, as well as sensor and robot coordinate frames changing over time. Furthermore, SEEREP provides an efficient HDF5-based storage system running on the robot during operation, compatible with ROS and the corresponding sensor message definitions. The compressed HDF5 data backend can be transferred efficiently to an application server with a running SEEREP query server providing gRPC interfaces with Protobuf and Flattbuffer message types. The query server can support high-level planning and reasoning systems in e.g. agricultural environments, or other partially unstructured environments that change over time. In this paper we show that SEEREP is much better suited for these tasks than a traditional GIS, which cannot handle the different types of robotic sensor data.

关键词： Three-dimensional displays Annotations Robot kinematics Semantics Robot sensing systems Cognition Planning

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Evolution of neural controllers for salamander-like locomotion

Evolution of neural controllers for salamander-like locomoti...

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sensor fusion and decentralized control in robotic systems II Conference

作者： Ijspeert, AJ Univ So Calif Dept Comp Sci Los Angeles CA 90879 USA

ISBN: (纸本)0819434329

This paper presents an experiment in which evolutionary algorithms are used for the development of neural controllers for salamander locomotion. The aim of the experiment is to investigate which kind of neural circuitry can produce the typical swimming and trotting gaits of the salamander, and to develop a synthetic approach to neurobiology by using genetic algorithms as design tool. A 2D bio-mechanical simulation of the salamander's body is developed whose muscle contraction is determined by the locomotion controller simulated as continuous-time neural networks. While the connectivity of the neural circuitry underlying locomotion in the salamander has not been decoded for the moment, the general organization of the designed neural circuits corresponds to that hypothesized by neurobiologists for the real animal. in particular, the locomotion controllers are based on a body central pattern generator (CPG) corresponding to a lamprey-like swimming controller as developed by Ekeberg,(1) and are extended with a limb CPG for controlling the salamander's body. A genetic algorithm is used to instantiate synaptic weights of the connections within the limb CPG and from the limb CPG to the body CPG given a high level description of the desired gaits. A set of biologically plausible controllers are thus developed which can produce a neural activity and locomotion gaits very similar to those observed in the real salamander. By simply varying the external excitation applied to the network, the speed, direction and type of gait can be varied.

关键词： Oscillators Gait analysis Device simulation Genetic algorithms Neurons Algorithm development Neuroscience Evolutionary algorithms Neural networks systems modeling

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Operators as information sources in sensor networks

Operators as information sources in sensor networks

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Kaupp, T Makarenko, A Kumar, S Upcroft, B Williams, S Univ Sydney ARC Ctr Excellence Autonomous Syst CAS Sydney NSW 2006 Australia

ISBN: (纸本)0780389123

This paper presents an approach of integrating human operators into a sensor network formed by a heterogeneous team of unmanned air and ground vehicles. Several objectives of human-network interaction are identified. The main focus of this work is on human-to-network information flow, i.e. human operators are regarded as information sources. It is argued that operators should make raw observations which are converted into the sensor network's common representation by a probabilistic model. The concepts are discussed in the context of an outdoor sensor network under development. Human operators contribute geometric feature information in the form of range and bearing observations. Visual feature properties are specified via meaningful class labels. A sensor model, represented as a Bayesian network, translates label observations into the system's representation. The model is also used to classify features as observed by robotic sensors.

关键词： sensor network human-network interaction decentralized data fusion classification

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Model-Free sensor fusion for Redundant Measurements Using Sliding Window Variance 22

Model-Free Sensor Fusion for Redundant Measurements Using Sl...

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22nd International Conference on control, Automation and systems (ICCAS)

作者： Makinen, P. Mustalahti, P. Launis, S. Mattila, J. Tampere Univ Automat Technol & Mech Engn Tampere Finland Sandv Min & Construct Oy Rock Technol & Drilling Tampere Finland

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.

关键词： sensor fusion Machine Vision sensor systems and Applications

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sensor Data fusion Using Unscented Kalman Filter for VOR-Based Vision Tracking System for Mobile Robots

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14th Annual Conference on Towards autonomous robotic systems (TAROS)

作者： Anjum, Muhammad Latif Ahmad, Omar Bona, Basilio Cho, Dong-il Dan Politecn Torino Dept Mech & Aerosp Engn DIMEAS Corso Duca Abruzzi 24 I-10129 Turin Italy Politecn Torino Dept Control & Comp Engn DAUIN I-10129 Turin Italy Seoul Natl Univ Dept Elect Engn & Comp Sci ASRI ISRC Seoul 151742 South Korea

ISBN: (纸本)9783662436455;9783662436448

This paper presents sensor data fusion using Unscented Kalman Filter (UKF) to implement high performance vestibulo-ocular reflex (VOR) based vision tracking system for mobile robots. Information from various sensors is required to be integrated using an efficient sensor fusion algorithm to achieve a continuous and robust vision tracking system. We use data from low cost accelerometer, gyroscope, and encoders to calculate robot motion information. The Unscented Kalman Filter is used as an efficient sensor fusion algorithm. The UKF is an advanced filtering technique which outperforms widely used Extended Kalman Filter (EKF) in many applications. The system is able to compensate for the slip errors by switching between two different UKF models built for slip and no-slip cases. Since the accelerometer error accumulates with time because of the double integration, the system uses accelerometer data only for the slip case UKF model. Using sensor fusion by UKF, the position and orientation of the robot is estimated and is used to rotate the camera mounted on top of the robot towards a fixed target. This concept is derived from the vestibulo-ocular reflex (VOR) of the human eye. The experimental results show that the system is able to track the fixed target in various robot motion scenarios including the scenario when an intentional slip is generated during robot navigation.

关键词： sensor fusion Unscented Kalman filter VOR Vision tracking systems

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