Abstract
Robustness and accuracy of real-time localisation and mapping systems have dramatically improved recently, thanks to advances in processing hardware and commoditisation of sensors such as RGB-D cameras and inertial measurement units. Related algorithms and their software implementations will be presented, with a recent focus on bringing together dense geometry and semantic, object-level scene understanding enabled by Deep Learning. The aim of these recent works is to bridge the sense-AI-gap and empower the next generation of mobile robots that need to plan and execute complex tasks in potentially cluttered, and dynamic environments, possibly in proximity of people. As an example application, recent work with drones will be shown, as used for instance in autonomous inspection or construction scenarios; which includes experiments in proximity or physical contact with structure.
Bio
Dr Stefan Leutenegger is a Senior Lecturer in Robotics in the Department of Computing at Imperial College London, where he leads the Smart Robotics Lab and furthermore co-directs research at the Dyson Robotics Lab. He has also co-founded SLAMcore, a spin-out company aiming at commercialisation of localisation and mapping solutions for robots and drones. Stefan has received a BSc and MSc in Mechanical Engineering with a focus on Robotics and Aerospace Engineering from ETH Zurich, as well as a PhD on “Unmanned solar airplanes: design and algorithms for efficient and robust autonomous operation”, completed in 2014.
Seminar Series
The Robotics Forum is creating a series of seminar events to hear from roboticists from within Imperial College, and from guest lecturers. This event is brought to you in combination with the Imperial College Robotics Society – ICRS