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Feedforward Mutual-Information Anomaly Detection: Application to autonomous Vehicles

Journal of autonomous Vehicles and Systems 2022年第4期2卷 041003页

作者： McKee, Sasha M. Haddadin, Osama S. Leang, Kam K. Dynamics and Autonomous Robotics Laboratory Department of Mechanical Engineering and Robotics Center University of Utah Salt Lake CityUT84112 United States L3Harris Technologies Salt Lake CityUT84116 United States

This paper describes a mutual-information (MI)-based approach that exploits a dynamics model to quantify and detect anomalies for applications such as autonomous vehicles. First, the MI is utilized to quantify the level of uncertainty associated with the driving behaviors of a vehicle. The MI approach handles novel anomalies without the need for data-intensive training;and the metric readily applies to multivariate datasets for improved robustness compared to, e.g., monitoring vehicle tracking error. Second, to further improve the response time of anomaly detection, current and past measurements are combined with a predictive component that utilizes the vehicle dynamics model. This approach compensates for the lag in the anomaly detection process compared to strictly using current and past measurements. Finally, three different MI-based strategies are described and compared experimentally: anomaly detection using MI with (1) current and past measurements (reaction), (2) current and future information (prediction), and (3) a combination of past and future information (reaction-prediction) with three different time windows. The experiments demonstrate quantification and detection of anomalies in three driving situations: (1) veering off the road, (2) driving on the wrong side of the road, and (3) swerving within a lane. Results show that by anticipating the movements of the vehicle, the quality and response time of the anomaly detection are more favorable for decision-making while not raising false alarms compared to just using current and past measurements. Copyright © 2024 by ASME.

关键词： autonomous vehicles

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Hierarchical Learned Risk-Aware Planning Framework for Human Driving Modeling

Hierarchical Learned Risk-Aware Planning Framework for Human...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Nathan Ludlow Yiwei Lyu John Dolan Robotics and Dynamics Laboratory Brigham Young University Provo Utah USA CMU Center for Autonomous Vehicle Research Carnegie Mellon University Pittsburgh USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents a novel approach to modeling human driving behavior, designed for use in evaluating autonomous vehicle control systems in a simulation environments. Our methodology leverages a hierarchical forward-looking, risk-aware estimation framework with learned parameters to generate human-like driving trajectories, accommodating multiple driver levels determined by model parameters. This approach is grounded in multimodal trajectory prediction, using a deep neural network with LSTM-based social pooling to predict the trajectories of surrounding vehicles. These trajectories are used to compute forward-looking risk assessments along the ego vehicle’s path, guiding its navigation. Our method aims to replicate human driving behaviors by learning parameters that emulate human decision-making during driving. We ensure that our model exhibits robust generalization capabilities by conducting simulations, employing real-world driving data to validate the accuracy of our approach in modeling human behavior. The results reveal that our model effectively captures human behavior, showcasing its versatility in modeling human drivers in diverse highway scenarios.

关键词： Road transportation Computational modeling Predictive models Data models Behavioral sciences Trajectory Planning

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Hierarchical Learned Risk-Aware Planning Framework for Human Driving Modeling

arXiv

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arXiv 2024年

作者： Ludlow, Nathan Lyu, Yiwei Dolan, John Robotics and Dynamics Laboratory Brigham Young University ProvoUT84602 United States CMU Center for Autonomous Vehicle Research Carnegie Mellon University Pittsburgh15289 United States

关键词： autonomous vehicles

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Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

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Nature Ecology and Evolution 2025年第6期9卷 1031-1042页

作者： Pringle, Stephen Dallimer, Martin Goddard, Mark A. Le Goff, Léni K. Hart, Emma Langdale, Simon J. Fisher, Jessica C. Abad, Sara-Adela Ancrenaz, Marc Angeoletto, Fabio Auat Cheein, Fernando Austen, Gail E. Bailey, Joseph J. Baldock, Katherine C. R. Banin, Lindsay F. Banks-Leite, Cristina Barau, Aliyu S. Bashyal, Reshu Bates, Adam J. Bicknell, Jake E. Bielby, Jon Bosilj, Petra Bush, Emma R. Butler, Simon J. Carpenter, Dan Clements, Christopher F. Cully, Antoine Davies, Kendi F. Deere, Nicolas J. Dodd, Michael Drinkwater, Rosie Driscoll, Don A. Dutilleux, Guillaume Dyrmann, Mads Edwards, David P. Farhadinia, Mohammad S. Faruk, Aisyah Field, Richard Fletcher, Robert J. Foster, Chris W. Fox, Richard Francksen, Richard M. Franco, Aldina M. A. Gainsbury, Alison M. Gardner, Charlie J. Giorgi, Ioanna Griffiths, Richard A. Hamaza, Salua Hanheide, Marc Hayward, Matt W. Hedblom, Marcus Helgason, Thorunn Heon, Sui P. Hughes, Kevin A. Hunt, Edmund R. Ingram, Daniel J. Jackson-Mills, George Jowett, Kelly Keitt, Timothy H. Kloepper, Laura N. Kramer-Schadt, Stephanie Labisko, Jim Labrosse, Frédéric Lawson, Jenna Lecomte, Nicolas de Lima, Ricardo F. Littlewood, Nick A. Marshall, Harry H. Masala, Giovanni L. Maskell, Lindsay C. Matechou, Eleni Mazzolai, Barbara McConnell, Alistair Melbourne, Brett A. Miriyev, Aslan Nana, Eric Djomo Ossola, Alessandro Papworth, Sarah Parr, Catherine L. Payo-Payo, Ana Perry, Gad Pettorelli, Nathalie Pillay, Rajeev Potts, Simon G. Prendergast-Miller, Miranda T. Qie, Lan Rolley-Parnell, Persie Rossiter, Stephen J. Rowcliffe, Marcus Rumble, Heather Sadler, Jon P. Sandom, Christopher J. Sanyal, Asiem Schrodt, Franziska Sethi, Sarab S. Shabrani, Adi Siddall, Robert Smith, Simón C. Snep, Robbert P. H. Soulsbury, Carl D. Stanley, Margaret C. Stephens, Philip A. Stephenson, P.J. Struebig, Matthew J. Studley, Matthew Svátek, Martin Tang, Gilbert Taylor, Nicholas K. Umbers, Kate D. L. Ward, Robert J. White, Patrick J. C. Whittingham, Mark J. Wich, Serge Williams, Christopher D. Yakubu, Ibrahim B. Yoh, Natalie Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury United Kingdom Centre for Environmental Policy Imperial College London London United Kingdom Department of Geography and Environmental Sciences Northumbria University Newcastle upon Tyne United Kingdom School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom Synthotech Ltd Milner Court Hornbeam Square Harrogate United Kingdom Mechanical Engineering Department University College London London United Kingdom HUTAN SWD Kota Kinabalu Malaysia Programa de Pós-Graduação em Gestão e Tecnologia Ambiental da Universidade Federal de Rondonópolis Rondonópolis Brazil Department of Engineering Harper Adams University Newport United Kingdom Applied Ecology Research Group School of Life Sciences Anglia Ruskin University Cambridge United Kingdom Centre for Ecology and Hydrology Penicuik United Kingdom Department of Life Sciences Imperial College London Silwood Park Campus Ascot United Kingdom Department of Urban and Regional Planning Faculty of Earth and Environmental Sciences Bayero University Kano Nigeria Greenhood Nepal Kathmandu Nepal Animal Rural & Environmental Sciences Nottingham Trent University Nottinghamshire United Kingdom School of Biological and Environmental Sciences Liverpool John Moores University Liverpool United Kingdom Lincoln Centre for Autonomous Systems University of Lincoln Lincoln United Kingdom Royal Botanic Garden Edinburgh Edinburgh United Kingdom School of Biological Sciences University of East Anglia Norwich Research Park Norwich United Kingdom Digital Ecology Limited Bristol United Kingdom School of Biological Sciences University of Bristol Bristol United Kingdom Department of Computing Imperial College London London United Kingdom Department of Ecology and Evolutionary Biology University of Colorado Boulder CO United States Faculty of Science Technology Engineering

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively. © The Author(s) 2025.

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Spacecraft heath monitoring using a biomimetic fault diagnosis scheme

Spacecraft heath monitoring using a biomimetic fault diagnos...

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作者： Garcia, Diego F. Perez, Andres E. Moncayo, Hever Rivera, Karina Betancur, Yomary DuPuis, Michael Mueller, Robert P. Department of Aerospace Engineering Flight Dynamics and Control Research Laboratory Embry-Riddle Aeronautical University Daytona BeachFL United States Research Engineer Robotics and Autonomous Systems Testing and Design Branch Swamp Works Laboratory United States Senior Technologist Exploration Research and Technology Programs Science and Technology Projects Division United States

This paper presents the design, development, and implementation of a bioinspired fault diagnosis scheme applied to a cold gas-based spacecraft *** proposed framework relies on the artificialimmune system metaphor with the goal of monitoring the health of the spacecraft by detecting subsystem upset conditions such as actuator *** dynamic inversion baseline controller with adaptation capabilities has been developed and implemented for attitude control of the spacecraft. The performance of the proposed health-monitoring scheme is determined by analyzing the system response under different actuator failures while the spacecraft is operated with and without adaptive augmentation. In both cases, the results show acceptable performance in terms of high detection activity and low false alarms with real-Time capabilities. The application of this artificial intelligence-based scheme to aerospace systems will provide a high impact on space exploration by increasing mission protection and performance. © 2018 by H. Moncayo. Published by the American Institute of Aeronautics and Astronautics.

关键词： Attitude control

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Spacecraft heath monitoring using a biomimetic fault diagnosis scheme

Spacecraft heath monitoring using a biomimetic fault diagnos...

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AIAA Information Systems-Infotech At Aerospace Conference, 2017

作者： Garcia, Diego F. Perez, Andres E. Moncayo, Hever Rivera, Karina Du Puis, Michael Mueller, Robert P. Department of Aerospace Engineering Flight Dynamics and Control Research Laboratory Embry-Riddle Aeronautical University United States Robotics and Autonomous Systems Testing and Design Branch NASA Kennedy Space Center Swamp Works Laboratory United States Science and Technology Projects Division NASA Kennedy Space Center Swamp Works Laboratory United States

ISBN: (纸本)9781624104497

This paper presents the design, development and implementation of a bio-inspired fault diagnosis scheme applied to a cold gas based spacecraft prototype. The proposed framework relies on the Artificial Immune System metaphor (AIS) with the goal of monitoring the health of the spacecraft by detecting subsystem upset conditions such as actuator malfunctions. A non-linear dynamic inversion (NLDI) baseline controller has been developed and implemented for attitude control of the spacecraft. The performance of the proposed health monitoring scheme is determined by analyzing the system response under different actuator failures and the results show acceptable performance in terms of high detection rate and low false alarms. The application of this artificial intelligent based scheme to aerospace systems will provide a high impact on space exploration by increasing mission protection and performance. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Attitude control

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Control laws development for a free-flying unmanned robotic system to support interplanetary bodies prospecting and characterization missions

Control laws development for a free-flying unmanned robotic ...

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AIAA Guidance, Navigation, and Control Conference, 2016

作者： Perez, Andres E. Moncayo, Hever Prazenica, Richard J. Zacny, Kris Mueller, Robert P. Ebert, Tom Dupuis, Michael Flight Dynamics and Control Research Laboratory Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Aerospace Engineering Department Embry-Riddle Aeronautical University Daytona BeachFL32114 United States Exploration Technology Group Honneybee Robotics Company CA United States Exploration Research and Technology Programs Science and Technology Projects Division NASA Kennedy Space Center FL United States Autonomous Flight Systems Lead Testing and Design Branch NASA Kennedy Space Center FL United States Robotics and Autonomous Systems Testing and Design Branch NASA Kennedy Space Center FL United States

ISBN: (数字)9781624103896

ISBN: (纸本)9781624103896

In situ Resource Utilization (ISRU) facilitates planetary exploration by drawing needed resources, such as water, from the local environment. However, the extreme nature of these environments require the development of advanced unmanned space systems integrated with sample-capture devices to achieve the ultimate goal of prospecting these resources. This paper presents the design, development and Hardware-in-the-Loop (HIL) simulation testing of guidance and tracking control laws for an autonomous small marsupial free-flyer prospector system. The control laws are based on an extended non-linear dynamic inversion (NLDI) approach and its implementation is illustrated through HIL simulation using a mathematical model of an autonomous vehicle research platform developed by NASA Kennedy Space Center. This vehicle has been designed to support the development, testing and validation of algorithms for safe, reliable, and scalable control space missions with minimal need for human intervention in complex, unstructured environments. The main objective of the control laws is to minimize 3-axis distances with respect to a desired trajectory and maintain stability and adequate performance in the presence of uncertainties. The performance of the control laws is evaluated during autonomous flight in terms of trajectory tracking errors, real-time execution on board the flight computer, and control activity at nominal and dynamically-changing conditions. The results show that for all mission cases investigated the control laws approach has desirable capabilities and is reliable for in-flight testing operation as a next step towards the validation and verification of this configuration. © 2016, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hardware-in-the-loop simulation

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Factorial design application to validate the performance of a wheeled mobile robot controlled via Internet

Factorial design application to validate the performance of ...

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2012 IEEE International Conference on Technologies for Practical Robot Applications, TePRA 2012

作者： Vargas, Hector Beristain, Gerson Olmedo, Edson Cuatle, Luis Medina, Esperanza Gabiño, Emilio Robotics and Control Laboratory Popular Autonomous University of the State of Puebla 11 wests 2304 Puebla Mexico Dynamics and Control Laboratory Mechanical and Aerospace Engineering Oklahoma State University United States

ISBN: (纸本)9781467308557

The article presents the application of a statistical method based on the factorial design to validate the performance of travel time on a circuit of a mobile robot teleoperated via Internet. When implementing the method we found the factors that significantly influence the performance of the robot, which improved distance control strategy. The analysis of the factors discarded the gender for selecting the operator to drive the remote robot. This method can be applied to teleoperate robots which need to validate its functionality and performance, identifying the factors that most influence the teleoperation and obtaining greater reliability. © 2012 IEEE.

关键词： Mobile robots

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Factorial design application to validate the performance of a wheeled mobile robot controlled via Internet

Factorial design application to validate the performance of ...

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IEEE International Conference on Technologies for Practical Robot Applications (TePRA)

作者： Hector Vargas Gerson Beristain Edson Olmedo Luis Cuatle Esperanza Medina Emilio Gabiño Robotics and Control Laboratory Popular Autonomous University of the State of Puebla Puebla Mexico Dynamics and Control Laboratory Mechanical and AeroSpace Engineering Oklahoma State University USA

关键词： Mobile robots Wheels Internet Three dimensional displays DC motors Educational institutions

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