Margarita Chli

Margarita Chli is an assistant professor and leader of the Vision for Robotics Lab at ETH Zürich in Switzerland. Chli is a leader in the field of computer vision and robotics and was on the team of researchers to develop the first fully autonomous helicopter with onboard localization and mapping. Chli is also the Vice Director of the Institute of Robotics and Intelligent Systems and an Honorary Fellow of the University of Edinburgh in the United Kingdom. Her research currently focuses on developing visual perception and intelligence in flying autonomous robotic systems.

Early life and education Chli grew up in Cyprus and Greece. She pursued her undergraduate degree at the University of Cambridge in the United Kingdom. She worked in the Robot Vision Group where she worked towards developing novel ways to manipulate data to enable efficient autonomous navigation of mobile devices. Since vision-based methods are the key to enabling autonomous navigation, Chli tried to address the challenges that lie in preserving precision while achieving efficient information processing. In 2013, Chli was awarded the Chancellor's Fellowship, and became an assistant professor at the Institute of Perception Action and Behavior at the University of Edinburgh. She held this prestigious fellowship for two years. Chli also participates in research towards the myCopter project whose goal is to design personal automated aerial transportation systems such that one could travel from work to home by air at low altitudes. Lastly, Chli's team develops methods to enable micro aerial vehicles to map out unknown environments through the SFly project (Swarm of micro flying robots). All of these projects require immense innovations in the field of computer vision and robotics, essentially demanding the ability that robots can handle large amounts of data in efficient ways to “see” their environments and respond quickly and autonomously. Chli's team aims to develop these intelligent systems with the capability of visual perception through the use of deep learning and robot collaboration.

Improving methods of computer vision Chli's early work helped to improve computer vision approaches to enable the construction of autonomous robotic systems. Chli first tackled the issue of simultaneous localization and mapping (SLAM) in which a robotic system has difficulty estimating its new and changing environment while also keeping track of its own location. Since dividing the map into smaller submaps would allow for individual parts of a scene to be processed independently and thus more efficiently, Chli created an innovative method to perform submap division on SLAM maps. She developed a method called BRISK (Binary Robust Invariant Scalable Key points) and it performed much faster and at a much lower computational cost compared to previous key point detection algorithms such as SURF and SIFT. The helicopter had a monocular camera as the only inertial sensory and was able to navigate in novel environments. Previously, multisensory integration was challenging due to sensory outages and differences in measurement rates and delays. Collaborative scene perception and mapping by a group of autonomous robots would serve a broad spectrum of uses from environmental data collection to surveillance and rescue. She proposed novel CNN-based image features for use in place recognition by creating regional representations of salient regions directly from convolutional layer activation. 2016 25 Women in Robotics You Need to Know 2016 International Conference on Robotics and Automation Best Associate Editor Award 2001-2005 Scholarship for outstanding qualifications, Trinity College, University of Cambridge, UK 2001-2005 Scholarship for outstanding performance, Cyprus State Scholarship Foundation Patrik Schmuck, Margarita Chli: CCM-SLAM: Robust and efficient centralized collaborative monocular simultaneous localization and mapping for robotic teams. J. Field Robotics 36(4): 763-781 (2019) Z. Chen, F. Maffra, I. Sa and M. Chli, "Only look once, mining distinctive landmarks from ConvNet for visual place recognition," 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, 2017, pp. 9–16, doi: 10.1109/IROS.2017.8202131. P. Schmuck and M. Chli, "Multi-UAV collaborative monocular SLAM," 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017, pp. 3863–3870, doi: 10.1109/ICRA.2017.7989445. S. Lynen, M. W. Achtelik, S. Weiss, M. Chli and R. Siegwart, "A robust and modular multi-sensor fusion approach applied to MAV navigation," 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, 2013, pp. 3923–3929, doi: 10.1109/IROS.2013.6696917. M. W. Achtelik, S. Lynen, S. Weiss, L. Kneip, M. Chli and R. Siegwart, "Visual-inertial SLAM for a small helicopter in large outdoor environments," 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura, 2012, pp. 2651–2652, doi: 10.1109/IROS.2012.6386270. S. Leutenegger, M. Chli and R. Y. Siegwart, "BRISK: Binary Robust invariant scalable keypoints," 2011 International Conference on Computer Vision, Barcelona, 2011, pp. 2548–2555, doi: 10.1109/ICCV.2011.6126542. M. Chli and A. J. Davison, "Automatically and efficiently inferring the hierarchical structure of visual maps," 2009 IEEE International Conference on Robotics and Automation, Kobe, 2009, pp. 387–394, doi: 10.1109/ROBOT.2009.5152530. Margarita Chli, Andrew J. Davison: Active matching for visual tracking. Robotics Auton. Syst. 57(12): 1173-1187 (2009)