Trustworthy Autonomous Systems
The area of Trustworthy Autonomous Systems is rapidly developing and there are demands to fill in this gap both with both in research and new robots, by combining the latest achievements in AI, Machine Learning and Robotics.
This multidisciplinary area brings together aspects of multiple sensor data fusion, intelligent sensing and navigation, building up maps, multi-robot collaboration, control, decision making and communications for robot platforms. From ground robots and small bots inspecting pipe networks to a single uncrewed aerial vehicle (UAV) or swarms of UAVs, these robots pose similar challenges and require both new theoretical methods and practical validation and experimentation, to standardisation and efficient computational and energy resources. Some of the key areas of the team are:
- Resilient and robust solutions for human-robot, human-UAVs interactions in changeable environments
- Human-robot teaming and interactions - both indoors, in enclosed spaces and outdoors
- Introduction of different levels of autonomy, e.g. UAVs for environmental monitoring, civil network infrastructure inspection, nuclear inspection and inspection of dangerous chemical areas, construction and infrastructure maintenance
- Digital twins
- Wildfire detection and localisation with UAVs
Sub Themes
- Field robotics and robotics for industrial and civil inspection
- Bio-inspired swarm robotics
- Trustworthy autonomy
Media
New fixed wing drone tech tested by the UK fire service for early detection of wildfires
Lancashire Fire and Rescue test Windracers’ drones for wildfire prevention
UK Firefighters Deploy Autonomous Drone Swarms in Groundbreaking Wildfire Prevention Test
Windracers and British Antarctic Survey arrive in Antarctica to test ULTRA UAV
Pilotless drones being tested in Antarctica for use in scientific research
Antarctica: Climate change impact to be mapped by robot plane | BBC News
Publications
S. Wang, J. Zhang, P. Wang, ,L. Law, R. Calinescu, L. Mihaylova: A Deep Learning-enhanced Digital Twin framework for Improving Safety and Reliability in Human-robot Collaborative Manufacturing. Robotics and Computer Integrated Manufacturing, Vol. 85: 102608, 2024.
J. Yan, Y. Zheng, J. Yang, L. Mihaylova, W. Yuan, Fuqiang Gu, PLPF-VSLAM: An indoor visual SLAM with adaptive fusion of point-line-plane features, Journal of Field Robotics, Vol. 41, No. 1, pp. 50-67, 2024
Y Lin, P Wang, Z Wang, S Ali, L Mihaylova, Towards Automated remote Sizing and Hot Steel Manufacturing with Image Registration and Fusion, Journal of Intelligent Manufacturing, 1-18, 2023
G. Caramente, G. Rassul, L. Mihaylova, BaSIS-Net: From Point Estimate to Predictive Distribution in Neural Networks, Transactions on Machine Learning Research, July 2024
H. Zhu, Y. Qiu, C. Yan, Y. Li, L. Mihaylova, H. Leung, An Adaptive Multi-sensor Fusion for Intelligent Vehicle Localization, IEEE Sensors, Vol. 24, No. 6, pp. 8798 - 8806, 2024
F. Candan, A. Beke, M. Mahfouf, L. Mihaylova, A Real-time Fuzzy Interacting Multiple-Model Velocity Obstacle Avoidance Approach for Unmanned Aerial Vehicles, Journal of Intelligent & Robotic Systems, Vol. 110, No. 61, pp. 1-13, 2024
R. Zhang, R. Worley, S. Edwards, J. Aitken, S. Anderson, L. Mihaylova, Visual Simultaneous Localization and Mapping for Sewer Pipe Networks Leveraging Cylindrical Regularity, IEEE Robotics and Automation Letters, Vol. 8, No. 6, pp. 3406 - 3413, June 2023
S. Edwards, R. Worley, R. Zhang, L. Mihaylova, J. Aitken, S. Anderson, Robot localization in feature-sparse sewer pipes using vision-based joint and manhole detections, Frontiers of Robotics and AI, Vol. 10, Article Number 1150508, March 6, 2023
X. Liu, L. Mihaylova, J. George, T. Pham, Gaussian Process Upper Confidence Bounds in Distributed Point Target Tracking over Sensor Networks, EEE Journal of Selected Topics in Signal Processing, Vol. 17, No. 1, pp. 295 - 310, 2023
X. Liu, M. Derakhshani, L. Mihaylova, S. Lambotharan, Risk-Aware Contextual Learning for Edge-Assisted Crowdsourced Live Streaming, IEEE Journal on Selected Areas in Communications, Special Issue on Multi-Tier Computing for Next Generation Wireless Networks, vol. 41, no. 3, pp. 740-754, March 2023
Y. Lin, P. Wang, Z. Wang, S. Ali, L. Mihaylova, Towards automated remote sizing and hot steel manufacturing with image registration and fusion, Journal of Intelligent Manufacturing , 15 November 2023
F. Candan, O. F. Dik, T. Kumbasar, M. Mahfouf, L. Mihaylova, Real-time Type-2 Fuzzy Control of an Unmanned Aerial Vehicle with Flexible Cable-Connected Payload, Algorithms for Multidisciplinary Applications. Algorithms for PID Controller - Special Issue, Vol. 16, No. 6, Article Number 273, 2023
C. Xue, Y. Huang, C. Zhao, L. Mihaylova, J. Chambers, A Gaussian-Generalized-Inverse-Gaussian Joint Distribution Based Adaptive MSCKF for Visual-Inertial Odometry Navigation, IEEE Transactions on Aerospace and Electronic Systems, Vol. 59, No. 3, pp. 2307-2328, June 2023.
K. Tsapparellas, N. Jelev, J. Waters, S. Brunswicker and L. Mihaylova, Vision-based Runway Detection and Landing for Unmanned Aerial Vehicle Enhanced Autonomy, In Proce. of the IEEE International Conf. on Mechatronics and Automation (ICMA), Harbin, Heilongjiang, China, pp. 239-246, 06-09 Aug 2023
J. Aitken, M. Evans, W. Worley, S. Edwards, R. Zhang, T. Dodd, L. Mihaylova, S. Anderson, Simultaneous Localisation and Mapping for Inspection Robots in Water and Sewer Pipe Networks: A Review, IEEE Access, Vol. 9, pp. 140173-140198, 2021.
