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A real-time indoor localization approach integrated with a Geographic Information System (GIS)

robotics AND autonomous SYSTEMS 2016年第PartB期75卷 475-489页

作者： Fernandez-Carames, Carlos Javier Serrano, F. Moreno, Vidal Curto, Belen Rodriguez-Aragon, J. F. Alves, Raul Fac Sci Robot & Soc Res Grp Salamanca 37008 Spain

Nowadays, accurate maps from mostly anywhere in the world can be obtained for free, with the exception of indoor spaces. However, the evidence seems to suggest that in the next few years indoor maps will be more and more available for anyone. Thus, profiting from the idea of easily obtainable indoor maps, we present a novel approach for real-time mobile robot localization that focuses on spatial reasoning at a high abstraction level. In order to manage and query existing indoor spatial models, we rely on the power of Geographic Information Systems (GIS) and spatial databases. Moreover, to extract symbolic information from the environment, we have developed a door detection system that fuses 2D laser and vision data. We have integrated these two ideas into an extended Kalman filter localization framework. Our proposal has been implemented and tested through autonomous navigation missions in real-world scenarios. Extensive experimental results are provided, which show robustness and accuracy concerning both door detection and localization. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Geographic Information System Door detection autonomous robotics Robot localization Integral Image Haar-like features

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Collective Tasks for a Flock of Robots Using Influence Factor

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2019年第2期94卷 439-453页

作者： Ordaz-Rivas, Erick Rodriguez-Linan, Angel Aguilera-Ruiz, Mario Torres-Trevino, Luis Univ Autonoma Nuevo Leon Fac Ingn Mecan & Elect Ave Univ S-N San Nicolas De Los Garza 66455 NL Mexico

In this paper, a form of steering a swarm of robots is presented using behavior local rules that depends on four parameters. These parameters are related with a general model of the behavior of social animals called repulsion, attraction orientation and influence. By simulations, a kinematic and dynamical math models of robots were made for testing its performance as a swarm and to know the impact of the parameters considering two tasks of location and navigation considering aggregation and flocking as a minimum condition that the swarm must have. An implementation was made building a flock of simple robots with hardware and software limitations. Some statistics to measure the performance of the swarm considering its covered area are proposed and analyze the impact of parameters on the swarm. Results of simulation are similar to the implementations as expected. The proposed behavior rules based on repulsion, attraction and orientation determine the formation of the swarm or the flock and influence emphasizes the principal task;in other words, associate a specific task with a specific perception or signal.

关键词： Swarm robotics Swarm intelligence autonomous robotics Emergent behavior Behavior-based

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Time-to-collision estimation from motion based on primate visual processing

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2005年第8期27卷 1279-1291页

作者： Galbraith, JM Kenyon, GT Ziolkowski, RW Los Alamos Natl Lab Los Alamos NM 87545 USA Univ Arizona Dept Elect Engn & Comp Sci Tucson AZ 85721 USA

A population coded algorithm, built on established models of motion processing in the primate visual system, computes the time-to-collision of a mobile robot to real-world environmental objects from video imagery. A set of four transformations starts with motion energy, a spatiotemporal frequency based computation of motion features. The following processing stages extract image velocity features similar to, but distinct from, optic flow;"translation" features, which account for velocity errors including those resulting from the aperture problem;and finally, estimate the time-to-collision. Biologically motivated population coding distinguishes this approach from previous methods based on optic flow. A comparison of the population coded approach with the popular optic flow algorithm of Lucas and Kanade against three types of approaching objects shows that the proposed method produces more robust time-to-collision information from a real world input stimulus in the presence of the aperture problem and other noise sources. The improved performance comes with increased computational cost, which would ideally be mitigated by special purpose hardware architectures.

关键词： motion processing autonomous robotics neuromorphic computing computer vision depth cues time-to-collision optic flow

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Visual-inertial navigation, mapping and localization: A scalable real-time causal approach

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2011年第4期30卷 407-430页

作者： Jones, Eagle S. Soatto, Stefano Univ Calif Los Angeles Los Angeles CA 90095 USA McKinsey INC New York NY USA

We describe a model to estimate motion from monocular visual and inertial measurements. We analyze the model and characterize the conditions under which its state is observable, and its parameters are identifiable. These include the unknown gravity vector, and the unknown transformation between the camera coordinate frame and the inertial unit. We show that it is possible to estimate both state and parameters as part of an on-line procedure, but only provided that the motion sequence is 'rich enough', a condition that we characterize explicitly. We then describe an efficient implementation of a filter to estimate the state and parameters of this model, including gravity and camera-to-inertial calibration. It runs in real-time on an embedded platform. We report experiments of continuous operation, without failures, re-initialization, or re-calibration, on paths of length up to 30 km. We also describe an integrated approach to 'loop-closure', that is the recognition of previously seen locations and the topological re-adjustment of the traveled path. It represents visual features relative to the global orientation reference provided by the gravity vector estimated by the filter, and relative to the scale provided by their known position within the map;these features are organized into 'locations' defined by visibility constraints, represented in a topological graph, where loop-closure can be performed without the need to re-compute past trajectories or perform bundle adjustment. The software infrastructure as well as the embedded platform is described in detail in a previous technical report.

关键词： Visual-inertial navigation simultaneous localization and mapping (SLAM) structure from motion vision-aided navigation vision-based navigation localization location recognition loop closure autonomous robotics assisted driving

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VPR-Bench: An Open-Source Visual Place Recognition Evaluation Framework with Quantifiable Viewpoint and Appearance Change

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INTERNATIONAL JOURNAL OF COMPUTER VISION 2021年第7期129卷 2136-2174页

作者： Zaffar, Mubariz Garg, Sourav Milford, Michael Kooij, Julian Flynn, David McDonald-Maier, Klaus Ehsan, Shoaib Univ Essex Sch Comp Sci & Elect Engn Colchester CO4 3SQ Essex England Delft Univ Technol Cognit Robot NL-2628 CD Delft Netherlands Queensland Univ Technol Sch Elect Engn & Comp Sci Brisbane Qld 4000 Australia Heriot Watt Univ Sch Engn & Phys Sci Smart Syst Grp Edinburgh EH14 4AS Midlothian Scotland

Visual place recognition (VPR) is the process of recognising a previously visited place using visual information, often under varying appearance conditions and viewpoint changes and with computational constraints. VPR is related to the concepts of localisation, loop closure, image retrieval and is a critical component of many autonomous navigation systems ranging from autonomous vehicles to drones and computer vision systems. While the concept of place recognition has been around for many years, VPR research has grown rapidly as a field over the past decade due to improving camera hardware and its potential for deep learning-based techniques, and has become a widely studied topic in both the computer vision and robotics communities. This growth however has led to fragmentation and a lack of standardisation in the field, especially concerning performance evaluation. Moreover, the notion of viewpoint and illumination invariance of VPR techniques has largely been assessed qualitatively and hence ambiguously in the past. In this paper, we address these gaps through a new comprehensive open-source framework for assessing the performance of VPR techniques, dubbed "VPR-Bench". VPR-Bench (Open-sourced at: ) introduces two much-needed capabilities for VPR researchers: firstly, it contains a benchmark of 12 fully-integrated datasets and 10 VPR techniques, and secondly, it integrates a comprehensive variation-quantified dataset for quantifying viewpoint and illumination invariance. We apply and analyse popular evaluation metrics for VPR from both the computer vision and robotics communities, and discuss how these different metrics complement and/or replace each other, depending upon the underlying applications and system requirements. Our analysis reveals that no universal SOTA VPR technique exists, since: (a) state-of-the-art (SOTA) performance is achieved by 8 out of the 10 techniques on at least one dataset, (b) SOTA technique in one community does not necessarily yield SOT

关键词： Visual place recognition SLAM autonomous robotics Robotic vision

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Predicting Millimeter Wave Radar Spectra for autonomous Navigation

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IEEE SENSORS JOURNAL 2010年第5期10卷 960-971页

作者： Jose, Ebi Adams, Martin Mullane, John Stephen Patrikalakis, Nicholas M. Singapore Technol Elect Ltd Singapore 569061 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore MIT Dept Mech Engn Cambridge MA 02139 USA

Millimeter Wave (MMW) radars are currently used as range measuring devices in applications such as automotive driving aids (Langer and Jochem, 1996), (Rohling and Mende, 1996), the mapping of mines (Brooker et al., 2005) and autonomous field robotics (Brooker, 2001), (Langer, 1996). This recent interest is largely due to the advantages MMW radars offer over other range measuring sensors, as their performance is less affected by dust, fog, rain or snow and ambient lighting conditions. MMW radars can provide received signal strength values, at all discrete range intervals, within the working range of the radar (Clark and Durrant-Whyte, 1997), (Scheding et al., 2002). The received power versus range spectra hence contain useful range to target information, but are also corrupted by noise. User defined stochastic algorithms can then be implemented, which exploit this rich data to improve object detection and mapping performance. This is in contrast to many other range measuring devices which typically internally threshold received signals, to provide single hard decisions only, on the estimated range to objects (Mullane, 2007). This paper addresses the issues of predicting the power-range spectra from MMW radars which use the Frequency Modulated Continuous Wave (FMCW) range estimation technique. This is important for two reasons. First, in automotive and autonomous robotic applications, such sensors are used in conjunction with vehicle navigation and map state estimation filters. This is so that (typically uncertain) vehicle motion knowledge can be optimally fused with the noisy sensor information, to infer estimates of the state of interest (typically, the vehicle's pose (position and orientation) and/or information of the surrounding object locations). Hence, it is essential that predicted power versus range spectra can be computed, to apply a Bayesian recursive estimation framework, based on previous measurements, and uncertain vehicle motion information. Second, it

关键词： Millimeter wave RADAR power range spectra autonomous robotics

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Automatic decision-making and reliability in robotic systems: some implications in the case of robot weapons

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AI & SOCIETY 2013年第4期28卷 431-441页

作者： Cordeschi, Roberto Sapienza Univ Rome Dept Philosophy V Carlo Fea 2 I-00186 Rome Italy

In this article, I shall examine some of the issues and questions involved in the technology of autonomous robots, a technology that has developed greatly and is advancing rapidly. I shall do so with reference to a particularly critical field: autonomous military robotic systems. In recent times, various issues concerning the ethical implications of these systems have been the object of increasing attention from roboticists, philosophers and legal experts. The purpose of this paper is not to deal with these issues, but to show how the autonomy of those robotic systems, by which I mean the full automation of their decision processes, raises difficulties and also paradoxes that are not easy to solve. This is especially so when considering the autonomy of those robotic systems in their decision processes alongside their reliability. Finally, I would like to show how difficult it is to respond to these difficulties and paradoxes by calling into play a strong formulation of the precautionary principle.

关键词： autonomous robotics Robot reliability Robot weapons Precautionary principle Risk decision-making Cybernetics Internet

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autonomous Learning of State Representations for Control: An Emerging Field Aims to autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations

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KUNSTLICHE INTELLIGENZ 2015年第4期29卷 353-362页

作者： Boehmer, Wendelin Springenberg, Jost Tobias Boedecker, Joschka Riedmiller, Martin Obermayer, Klaus Tech Univ Berlin Neural Informat Proc Grp Sekr MAR 5-6Marchstr 23 D-10587 Berlin Germany Univ Freiburg Machine Learning Lab Freiburg Germany

This article reviews an emerging field that aims for autonomous reinforcement learning (RL) directly on sensor-observations. Straightforward end-to-end RL has recently shown remarkable success, but relies on large amounts of samples. As this is not feasible in robotics, we review two approaches to learn intermediate state representations from previous experiences: deep auto-encoders and slow-feature analysis. We analyze theoretical properties of the representations and point to potential improvements.

关键词： End-to-end reinforcement learning Representation learning Deepauto-encoder networks Slow feature analysis autonomous robotics

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Holistic visual encoding of ant-like routes: Navigation without waypoints

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ADAPTIVE BEHAVIOR 2011年第1期19卷 3-15页

作者： Baddeley, Bart Graham, Paul Philippides, Andrew Husbands, Philip Univ Sussex Sch Informat Ctr Computat Neurosci & Robot Brighton E Sussex England

It is known that ants learn long visually guided routes through complex terrain. However, the mechanisms by which visual information is first learned and then used to control a route direction are not well understood. In this article, we propose a parsimonious mechanism for visually guided route following. We investigate whether a simple approach, involving scanning the environment and moving in the direction that appears most familiar, can provide a model of visually guided route learning in ants. We implement view familiarity as a means of navigation by training a classifier to determine whether a given view is part of a route and using the confidence in this classification as a proxy for familiarity. Through the coupling of movement and viewing direction, a familiar view specifies a familiar direction of viewing and thus a familiar movement to make. We show the feasibility of our approach as a model of ant-like route acquisition by learning a series of nontrivial routes through an indoor environment using a large gantry robot equipped with a panoramic camera.

关键词： Insect navigation route learning view-based homing image classification autonomous robotics

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On Passivity-Shortage of Human Operators for A Class of Semi-autonomous Robotic Swarms

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IFAC-PapersOnLine 2019年第34期51卷 21-27页

作者： Surya Atman, Made Widhi Noda, Kosei Funada, Riku Yamauchi, Junya Hatanaka, Takeshi Fujita, Masayuki Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan Division of Electrical Electronic and Information Engineering Graduate School of Engineering Osaka University Osaka Japan

This paper analyzes perceived workload and passivity-shortage of human operators for a class of semi-autonomous robotic swarms. First, we briefly introduce the passivity-short-based architecture presented in one of our previous works, which guarantees human-enabled motion synchronization to desired position/velocity references under the assumption that the human operator's thought process is a passivity-short system. It is observed that changes in parameter affects the visual feedback to the operator and also the complexity of the setups. Through user-studies using a human-in-the-loop simulator and questionnaires, we observe an increase in the perceived workload of the human operator for more complex setups. The result imposes the trade-off for less workload vs. clarity of the robotic swarms’ information to the human operator. Furthermore, through non-parametric system identification on data from user-studies, it is observed that all obtained models of the participants have the passivity-short property. © 2019

关键词： Visual servoing Economic and social effects Personnel robotics Surveys Visual communication autonomous robotics Co operative control Desired position Human in the loop Non parametric Robotic swarms Thought process Visual feedback

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