ACE-OPS: From Autonomy to Cognitive assistance in Emergency OPerationS

Lead Research Organisation: University of Oxford
Department Name: Computer Science

Abstract

The vision of this collaborative multi-centre project is to safeguard and transform current operation protocols of emergency teams by providing sensing, situation awareness, cognitive assistance and mobile autonomy capabilities working synergistically as a single system. Statistics collected by the Home Office report 346 fire related fatalities in England during 2016/2017, the highest figure since 2011/12. Over a 10-year period in USA, 2775 firefighters died on duty. Where there is a need to save and evacuate people from a burning or flooded building, it is important for the chief incident commander to have increased situational awareness and to be able to effectively coordinate the rescue operation, and for individual responders to have enhanced visibility of surrounding hazards and dangers. To this end, we need to combine UK-based expertise in mobile autonomy and people localisation, with internationally leading expertise on welfare monitoring and cognitive assistance at the Univ. of Virginia, and on robotic vision applied to aerial vehicles at the Queensland University of Technology.

The proposed work involves four distinct research directions: 1) providing an integrated system for situation awareness that involves localisation of the emergency responders, monitoring of their welfare and mapping of the dynamically changing environment; 2) exploring how situation awareness information should be fed into cognitive assistance tools, in order to provide helpful triggers and alerts to the incident commander and their team; 3) introducing various levels of autonomy enabling aerial vehicles to simultaneously perform tasks of mapping, communication and localisation; and 4) integrating the above capabilities and building the first end-to-end response system that implements the full feedback loop from sensor acquisition to emergency responders and back to sensor actuation. Sensors on people's wearable devices together with sensors mounted on aerial vehicles will contribute to data acquisition for welfare, location and environment monitoring. This in turn will provide input to cognitive assistance for emergency response teams, helping them to assess the situation. They will then in turn provide feedback to sensor systems to prioritise monitoring of specific areas, people or tasks, thus dynamically influencing the next round of situation awareness, and so on. This feedback loop will be a step change providing a whole new approach to safety for emergency responders.

Planned Impact

First responders operate in extremely hazardous and dangerous conditions, risking their lives and wellbeing to save others. In the UK, 14 firefighters lost their lives over the ten year period 2003-2014. Internationally, over the same period, 2775 firefighters died in the USA.
The ambulance and police services similarly face hostile and perilous working conditions. The challenges faced by first responders motivates the need for an urgent and internationally guided effort to improve the state-of-the-art in terms of situational awareness, reducing first responder deaths and injuries. In turn, better operating knowledge translates to improved outcomes for victim rescue, impacting the broader public through faster and more targetted responses. This has widespread social and welfare benefits. To achieve these goals, our proposed project includes strong support from Dstl and the Home Office to incorporate technological advances into first responder practice in the UK. More broadly, they will also support the project through exposure at the International Forum to Advance First Responder Innovation (IFAFRI) which links Australia, Canada, the European Commission, Finland, Germany, Israel, Japan, Mexico, New Zealand, Singapore, Spain, Sweden, The Netherlands, United Kingdom, and the United States. Through existing partnerships, we have strong links with the National Fire Chiefs Council (NFCC) which is the umbrella organization for informing government and formulating best operating practice and guidance. At a regional level, we have an ongoing relationship with the Hampshire Fire and Rescue Service, whose facilities and expertise we will use for testing. Internationally, in the United States, the National Institute of Standards and Technology is leading the Public Safety Innovation Accelerator Program which seeks to transform first responder protocol and safety through advanced technology. Trigoni and Stakonovic both lead grants funded by NIST and this provides an ideal mechanism for widespread impact to the first responder community in the United States. Through NIST, UVA and its associated stakeholder conferences, we will disseminate key findings of this project and work closely with US services. We will work with these and other partners to inform technology design, test and refine implementations and create a novel platform that will provide the first end-to-end first responder technology for cognitive, autonomous and enhanced situational awareness and control. The ultimate successful impact of this project will be the adoption of the designed technology which leads to a reduction in fatalities and injuries, both to first responders and the general public.

In terms of economic impact, improved situational awareness and response can lead to better management of disasters and incidents. Benefits of improved safety could lead to lower first responder time loss due to hospitalization etc. Better monitoring of welfare can also lead to more targeted and informed responses to factors such as dehydration and heat stress. It is also likely that the technology created will generate new intellectual property, with consequent opportunity for licensing, spinout and commercial exploitation.

Workshops will be run at the end of years 2 and 3 to disseminate findings and network with key partners, academic, governmental and from the first responder community. We will also pursue high impact publications in leading conferences and journals e.g. AAAI, IJCAI, ICRA, NIPS, TPAMI etc., to disseminate our novel research.

The national and international importance of this project makes it a high profile demonstration of how the UK research councils are funding state-of-the-art techniques for improving rescue. As such, this Centre-to-Centre project will attract the interest of the wider public, which will be exploited through a dedicated, media-rich website, frequent press releases and feature articles in the popular press.

Publications

10 25 50
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Gammel JD (2021) Asymptotically optimal sampling-based motion planning methods in Annual Review of Control, Robotics, and Autonomous Systems

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Chen C (2022) Learning Selective Sensor Fusion for State Estimation in IEEE Transactions on Neural Networks and Learning Systems

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Chen C (2021) DynaNet: Neural Kalman Dynamical Model for Motion Estimation and Prediction. in IEEE transactions on neural networks and learning systems

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Saputra M (2022) Graph-Based Thermal-Inertial SLAM With Probabilistic Neural Networks in IEEE Transactions on Robotics

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Miñano S (2023) Through Hawks' Eyes: Synthetically Reconstructing the Visual Field of a Bird in Flight. in International journal of computer vision

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Gammell JD (2020) Batch Informed Trees (BIT*): Informed asymptotically optimal anytime search in International Journal of Robotics Research (IJRR)

 
Description We have addressed many of the challenges linked to autonomous systems for handling multiple, and often conflicting, operational needs in emergency scenarios.

More specifically, the key achievements linked to the project's objectives are:
1) novel localisation and scene understanding algorithms and methodologies that are robust to challenging low visibility and smoke-filled environments;
2) unique datasets on indoor scenarios featuring multiple sensors and collected across different mobile platforms
3) robust task and motion planning algorithms for autonomous vehicles
4) open sourced software libraries for planning
Exploitation Route Use of open sourced code by other research groups
Use of datasets by other research groups
Research outcomes could be the basis for companies to provide safer apparatus for emergency responders
Sectors Digital/Communication/Information Technologies (including Software)

 
Description AWS Funded Project: Autonomy in Blue Light Emergency Services
Amount £330,000 (GBP)
Organisation Amazon.com 
Department Amazon Web Services
Sector Private
Country United States
Start 10/2020 
End 04/2024
 
Title OdomBeyondVision: An Indoor Multi-modal Multi-platform Odometry Dataset Beyond the Visible Spectrum 
Description An Indoor Multi-modal Multi-platform Odometry Dataset Beyond the Visible Spectrum. This paper presents a multimodal indoor odom- etry dataset, OdomBeyondVision, featuring multiple sensors across the different spectrum and collected with different mobile platforms. Not only does OdomBeyondVision contain the traditional navigation sensors, sensors such as IMUs, mechanical LiDAR, RGBD camera, it also includes several emerging sensors such as the single-chip mmWave radar, LWIR thermal camera and solid-state LiDAR. With the above sensors on UAV, UGV and handheld platforms, we respectively recorded the multimodal odometry data and their movement trajectories in various indoor scenes and different illumination conditions. We release the exemplar radar, radar-inertial and thermal- inertial odometry implementations to demonstrate their results for future works to compare against and improve upon. The full dataset including toolkit and documentation is publicly avail- able at: https://github.com/MAPS-Lab/OdomBeyondVision. Paper describing dataset is here: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9981865 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact Use of dataset by other researchers 
URL https://github.com/MAPS-Lab/OdomBeyondVision
 
Title Thermal, Visual, Lidar Multi-modal dataset 
Description This dataset consists of trajectories collected by a multimodal (thermal, radar, inertial, visual, lidar) platform. The data was collected both by both handheld and robotic platforms. The majority of datasets with thermal imagery have been collected by autonomous vehicles (self-driving cars), whereas this dataset is from indoor environments (university and college buildings). 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? No  
Impact This dataset serves as the basis for a number of papers in thermal-inertial odometry from the CPS group. This dataset will be released later this year (2021) as a public dataset. 
 
Description Collaboration on robust depth estimation in challenging illumination conditions 
Organisation Queensland University of Technology (QUT)
Country Australia 
Sector Academic/University 
PI Contribution Our Oxford CPS group proposed novel depth estimation approaches for challenging illumination conditions (day and night) and co-authored a paper with QUT
Collaborator Contribution Our partner provided valuable feedback into the proposed algorithms and helped co-author a paper accepted at CoRL 2022
Impact A published research paper at the 2023 Conference on Robot Learning
Start Year 2022
 
Description Collaboration with researchers from other universities to collect a multi modal indoor odometry dataset 
Organisation University of Edinburgh
Department School of Informatics Edinburgh
Country United Kingdom 
Sector Academic/University 
PI Contribution We contributed to generating and curating data for the odometry dataset, OdomBeyondVision, featuring multiple sensors across the different spectrum and collected with different mobile platforms. Not only does OdomBeyondVision contain the traditional navigation sensors, sensors such as IMUs, mechanical LiDAR, RGBD camera, it also includes several emerging sensors such as the single-chip mmWave radar, LWIR thermal camera and solid-state LiDAR. With the above sensors on UAV, UGV and handheld platforms, we respectively recorded the multimodal odometry data and their movement trajectories in various indoor scenes and different illumination conditions. We release the exemplar radar, radar-inertial and thermal-inertial odometry implementations to demonstrate their results for future works to compare against and improve upon. The full dataset including toolkit and documentation is publicly available at: https://github.com/MAPS-Lab/OdomBeyondVision.
Collaborator Contribution Our partners contributed to analysing the dataset and co-authoring the paper that described the dataset.
Impact A unique dataset including toolkit and documentation publicly available at: https://github.com/MAPS-Lab/OdomBeyondVision
Start Year 2020
 
Description Collaboration with researchers from other universities to collect a multi modal indoor odometry dataset 
Organisation University of Liverpool
Country United Kingdom 
Sector Academic/University 
PI Contribution We contributed to generating and curating data for the odometry dataset, OdomBeyondVision, featuring multiple sensors across the different spectrum and collected with different mobile platforms. Not only does OdomBeyondVision contain the traditional navigation sensors, sensors such as IMUs, mechanical LiDAR, RGBD camera, it also includes several emerging sensors such as the single-chip mmWave radar, LWIR thermal camera and solid-state LiDAR. With the above sensors on UAV, UGV and handheld platforms, we respectively recorded the multimodal odometry data and their movement trajectories in various indoor scenes and different illumination conditions. We release the exemplar radar, radar-inertial and thermal-inertial odometry implementations to demonstrate their results for future works to compare against and improve upon. The full dataset including toolkit and documentation is publicly available at: https://github.com/MAPS-Lab/OdomBeyondVision.
Collaborator Contribution Our partners contributed to analysing the dataset and co-authoring the paper that described the dataset.
Impact A unique dataset including toolkit and documentation publicly available at: https://github.com/MAPS-Lab/OdomBeyondVision
Start Year 2020
 
Description Collaborative work on robust indoor mapping with low cost mmWave radar 
Organisation University of Virginia (UVa)
Country United States 
Sector Academic/University 
PI Contribution My research group (X. Lu, S. Rosa, P. Zhao, B. Wang, C. Chen, A. Markham and N. Trigoni) carried out the bulk of the research work, including the design, implementation and evaluation of milliMap, a single chip millimetre wave radar based indoor mapping system targeted towards low visibility environments. The work started earlier (2019) and initially was funded by the Mobile Autonomy Research Grant (supporting co-authors C. Lu and S. Rosa) and in its latter phase (end 2019- first half of 2020) by ACE-OPS (supporting co-author C. Chen). The work was refined with C. Chen's help in early 2020 following feedback from Mobisys reviewers.
Collaborator Contribution Prof. John A Stankovic contributed to research discussions with researchers in my group. The collaboration started earlier in 2018 when he spent his sabbatical at Oxford working with our group (Cyber Physical Systems) and is ongoing until now - albeit with slightly different focus- in the context of ACE-OPS. Prof John Stankovic had frequent discussions with our group, including how to design experiments to validate the proposed indoor mapping method. He also provided feedback on initial drafts of the paper.
Impact Paper publication: "See through smoke: robust indoor mapping with low-cost mmWave radar" Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services
Start Year 2018
 
Description Collaborative work on robust indoor mapping with low cost mmWave radar 
Organisation University of Virginia (UVa)
Country United States 
Sector Academic/University 
PI Contribution My research group (X. Lu, S. Rosa, P. Zhao, B. Wang, C. Chen, A. Markham and N. Trigoni) carried out the bulk of the research work, including the design, implementation and evaluation of milliMap, a single chip millimetre wave radar based indoor mapping system targeted towards low visibility environments. The work started earlier (2019) and initially was funded by the Mobile Autonomy Research Grant (supporting co-authors C. Lu and S. Rosa) and in its latter phase (end 2019- first half of 2020) by ACE-OPS (supporting co-author C. Chen). The work was refined with C. Chen's help in early 2020 following feedback from Mobisys reviewers.
Collaborator Contribution Prof. John A Stankovic contributed to research discussions with researchers in my group. The collaboration started earlier in 2018 when he spent his sabbatical at Oxford working with our group (Cyber Physical Systems) and is ongoing until now - albeit with slightly different focus- in the context of ACE-OPS. Prof John Stankovic had frequent discussions with our group, including how to design experiments to validate the proposed indoor mapping method. He also provided feedback on initial drafts of the paper.
Impact Paper publication: "See through smoke: robust indoor mapping with low-cost mmWave radar" Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services
Start Year 2018
 
Description International Collaboration on Deep Odometry Systems on Edge with EKF-LoRa Backend for Real-Time Indoor Positioning 
Organisation Monash University
Country Australia 
Sector Academic/University 
PI Contribution - 6 months of time contribution for research of two graduate researchers and two grant PIs (Niki Trigoni and Andrew Markham), including supervision, research discussions, dataset generation, paper writing etc.
Collaborator Contribution ~ 3 months of time contribution for joint research between our group at the University of Oxford and partners at the University of Virginia (US), Monash University (Indonesia) and University of Edinburgh (UK) - Discussion of research ideas and results - given their prior experience in the same field - Co-authoring of paper
Impact A paper submitted to 1st workshop on cyber physical systems for emergency response. Paper has been accepted and will be presented in May 2022 at the workshop.
Start Year 2021
 
Description International Collaboration on Deep Odometry Systems on Edge with EKF-LoRa Backend for Real-Time Indoor Positioning 
Organisation University of Edinburgh
Country United Kingdom 
Sector Academic/University 
PI Contribution - 6 months of time contribution for research of two graduate researchers and two grant PIs (Niki Trigoni and Andrew Markham), including supervision, research discussions, dataset generation, paper writing etc.
Collaborator Contribution ~ 3 months of time contribution for joint research between our group at the University of Oxford and partners at the University of Virginia (US), Monash University (Indonesia) and University of Edinburgh (UK) - Discussion of research ideas and results - given their prior experience in the same field - Co-authoring of paper
Impact A paper submitted to 1st workshop on cyber physical systems for emergency response. Paper has been accepted and will be presented in May 2022 at the workshop.
Start Year 2021
 
Description International Collaboration on Deep Odometry Systems on Edge with EKF-LoRa Backend for Real-Time Indoor Positioning 
Organisation University of Virginia (UVa)
Country United States 
Sector Academic/University 
PI Contribution - 6 months of time contribution for research of two graduate researchers and two grant PIs (Niki Trigoni and Andrew Markham), including supervision, research discussions, dataset generation, paper writing etc.
Collaborator Contribution ~ 3 months of time contribution for joint research between our group at the University of Oxford and partners at the University of Virginia (US), Monash University (Indonesia) and University of Edinburgh (UK) - Discussion of research ideas and results - given their prior experience in the same field - Co-authoring of paper
Impact A paper submitted to 1st workshop on cyber physical systems for emergency response. Paper has been accepted and will be presented in May 2022 at the workshop.
Start Year 2021
 
Description International Collaboration on Task and Motion Planning 
Organisation Rice University
Country United States 
Sector Academic/University 
PI Contribution ESP (Estimation, Search and Planning) group from the Oxford Robotics Institute, University of Oxford, collaborated with researchers from Rice University and from the Jet Propulsion Laboratory California Institute of Technology on novel path planning algorithms for mobile robots. The collaboration led to a joint paper and open source code.
Collaborator Contribution Research ideas and co-authors of joint paper.
Impact Novel path planning algorithms and methodologies
Start Year 2021
 
Title EIRM* 
Description Publish path planning algorithm to open source library of planning algorithms 
Type Of Technology Software 
Year Produced 2022 
Open Source License? Yes  
Impact Enhancement of know how on planning algorithms, sharing, and opportunities for further advances 
URL http://ompl.kavrakilab.org/
 
Title PDT 
Description Publish open source library for performing and analysing planning experiments 
Type Of Technology Software 
Year Produced 2022 
Open Source License? Yes  
Impact Sharing of planning methodology with other research groups and industry to be applied and improved in multiple applications 
URL https://robotic-esp.com/code/pdt
 
Title TMIT* 
Description Publish TAMP algorithm open source 
Type Of Technology Software 
Year Produced 2022 
Open Source License? Yes  
Impact Diverse use by by other research groups in academia and industry 
URL https://robotic-esp.com/code/tmitstar/
 
Description ACE-OPS Intl Collaboration Progress Meeting 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact International Collaboration Progress Meerting

Introduction and update from Niki Trigoni from Computer Science (Univ. of Oxford) on the Ace-Ops project. Talk/update by Rowan Border from Oxford Robotics Institute on latest research on multi-motion estimation. Talk by Qian Xie from Computer Science on Thermal based Pedestrian detection. Talk by Vu Tran from Computer Science on Two Sided Data Driven UWB error Mitigation for indoor localisation. Talk by Arif Rahman from the university of Virginia will present on "First responders and CPR". Talk by Lahiru Wijayasingha from the University of Virginia on the use of Augmented reality (smart Glasses) to aid a first responder. Andrew Markham from Computer Science presents plans for Ace-Ops virtual workshop later in May 2022.
Final round up and next steps by Niki Trigoni.
Year(s) Of Engagement Activity 2022
 
Description ACE-OPS Partner Mtg 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Each research group presented their progress and discussed future directions for international collaboration.

Several research talks were given by Niki Trigoni, Andrew Markham, Risqi Utama Saputra (Cyber Physical Systems, Univ. of Oxford), Jonathan Gammell and Rowan Border (Oxford Robotics Inst., Univ. of Oxford) and Jack Stankovic (Univ. of Virginia).
Year(s) Of Engagement Activity 2021
URL http://aceops.cs.ox.ac.uk/
 
Description ESA Workshop on AI for Space Operations 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Third sector organisations
Results and Impact Workshop discussion
Year(s) Of Engagement Activity 2020
 
Description Invited Talk at Cornell University 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talk to the Department of Computer Science at Cornell University in the US
Year(s) Of Engagement Activity 2021
 
Description Invited Talk at ETH Zurich 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited Talk for the Institute for Dynamic Systems and Control, ETH Zurich
Year(s) Of Engagement Activity 2022
 
Description Invited Talk at IEEE/RSJ IROS Workshop 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited Talk at IEEE/RSJ IROS Workshop on Evaluating Motion Planning Performance
Year(s) Of Engagement Activity 2022
 
Description Invited Talk at Space @ Oxford Week 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Invited talk at the Space@Oxford event
Year(s) Of Engagement Activity 2021
 
Description Invited Talk at TU Berlin 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talk to the LIS group at TU Berlin
Year(s) Of Engagement Activity 2021
URL http://www.youtube.com/watch?v=cJIP2ad5Hwg
 
Description Invited Talk at TU Berlin 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talk to the LIS group at TU Berlin
Year(s) Of Engagement Activity 2021
URL http://www.youtube.com/watch?v=cJIP2ad5Hwg
 
Description Invited Talk at University of British Columbia 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talk to the Department of Mechanical Engineering at the University of British Columbia in Canada
Year(s) Of Engagement Activity 2021
 
Description Invited talk at University of Cambridge, Systems Research Group Seminar 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact Invited talk "Scene understanding in emergency response scenarios" - This talk was intended to share with research community the challenges presented in setting up cyber physical systems in emergency scenarios. Advances in sensing, robotics and machine learning have recently led to scene understanding algorithms that have transformed smart city applications, like transport, healthcare and energy. However this technology has found slower uptake in the challenging world of blue light emergency response. In this talk I will present some of the key challenges faced by intelligent sensor systems in emergency situations including dynamic changes of the environment, lack of preinstalled network or sensor infrastructure, and operation in previously unseen and unpredictable situations. I will then present recent multi-modal sensing approaches to addressing these challenges.
Year(s) Of Engagement Activity 2022
 
Description Invited workshop talk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talk on my research at workshop
Year(s) Of Engagement Activity 2020
 
Description Invited workshop talk 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited talk on my research at workshop
Year(s) Of Engagement Activity 2020
 
Description Joint ACE-OPS workshop - autonomy for emergency response: University of Oxford (UK(), Queensland University of Technology (Australia) and University of Virginia (USA) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact This workshop included a mix of presentations and discussions on state of the art methods for emergency response, combining approaches to wearable- and robot-based perception and cognitive assistance. These included talks and discussions on visual, visual-inertial and multi-motion odometry, mobile autonomy and cognitive assistance. Further discussion uncovered interesting opportunities for joint collaboration (remote due to covid), which members of the workshops are now pursuing independently.
Year(s) Of Engagement Activity 2021
 
Description Keynote at Conference (SensorNets 2022) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Keynote Title: Scene understanding in emergency applications: challenges and lessons learnt

Abstract: Emergency situations present some of the most challenging and unusual scenarios for sensing and scene understanding; yet, it is in these situations, where situation awareness is of paramount importance and where technology is needed the most to help protect human lives. In this talk, I will present some of the key challenges faced by sensing and machine learning algorithms in emergency situations, including lack of pre-installed sensing infrastructure, lack of training data, sensor failure, and limited visibility and connectivity. I will then present recent research directions that we have pursued to address these challenges including multi-modal sensing, cross modality training and human-robot interaction.
Year(s) Of Engagement Activity 2022
URL https://www.youtube.com/watch?v=HMOGr9YtA64
 
Description Organisation Activities for New Workshop (Cyber Physical Systems for Emergency Response - CPS-ER) by Andrew Markham, Niki Trigoni and Jack Stankovic 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Organisation of a new workshop (Cyber Physical Systems for Emergency Response - CPS-ER) by Andrew Markham, Niki Trigoni and Jack Stankovic

This is a new workshop colocated with CPS-IOT Week 2022 (https://sites.google.com/view/cps-er/) which was organised by the grant's PIs in order to promote awareness and disseminate research outputs in the area of cyber physical systems for emergency response.

Several meetings have taken place to organise this event, review papers and finalise accepted papers, as well as coordinate with the organisers of the CPS-IOT Week.

The workshop itself will be held virtually in May 2022.
Year(s) Of Engagement Activity 2022
 
Description Panel discussion at IROS Workshop 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Panel discussion at IEEE/RSJ IROS Workshop on Evaluating Motion Planning Performance
Year(s) Of Engagement Activity 2022
 
Description Working collaboration group between University of Oxford CS and Engineering Depts and University of Virginia 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact This was a workshop across three research groups, University of Oxford Cyber Physical Systems Group, Oxford Robotics Institute (ORI) and University of Virginia, where representatives of these groups gave short 20 minute talks about ongoing work in the ACE-OPS project. Members of the Cyber Physical Systems Group discussed ongoing work on learning to localise with inertial sensors, selective sensor fusion and sequential invariant domain adaptation. Members of the ORI Group presented ongoing work on best view planning for 3D reconstruction and multimotion visual odometry. Members of the University of Virginia group focused on cognitive assistance for first responders. This was followed by a discussion on the application of the above research directions to emergency response and linkages across the research threads.
Year(s) Of Engagement Activity 2020
 
Description Workshop on Sensing, Estimating and Understanding the Dynamic World 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact ICRA workshop on multimotion estimation
Year(s) Of Engagement Activity 2020
URL https://robotics.sydney.edu.au/icra-workshop/
 
Description Workshop on Sensing, Estimating and Understanding the Dynamic World 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact ICRA workshop on multimotion estimation
Year(s) Of Engagement Activity 2020
URL https://robotics.sydney.edu.au/icra-workshop/
 
Description Workshop organisation: CPS-ER 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact SCOPE
Emergency responders operate in dangerous conditions. They need to deploy rapidly to an event, and make decisions under stressful and information-limited conditions, at risk to themselves. Advances in autonomous systems e.g. location, semantics, vital sign monitoring, robotic exploration, high level situational awareness, can help to provide more information, both in real-time, and also for post-event reporting/analysis. This half-day workshop seeks to bring an interested community together to foster interaction, collaboration and participation in this important area.

The new workshop (Cyber Physical Systems for Emergency Response - CPS-ER) was organised by PIs Andrew Markham and Niki Trigoni, and external collaborator, Jack Stankovic (Univ. of Virginia). This was a new workshop colocated with CPS-IOT Week 2022 (https://sites.google.com/view/cps-er/) which was organised by the grant's PIs in order to promote awareness and disseminate research outputs in the area of cyber physical systems for emergency response.
Year(s) Of Engagement Activity 2022
URL https://sites.google.com/view/cps-er/