Spatial Perception for Mobile Robots
Stefan Leutenegger
(Imperial College, UK)
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. I have been working on related algorithms and
their software implementations, with a more recent focus on bringing
together dense geometry and semantic, object-level scene understanding.
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. Example applications to be shown include
inspection and autonomous construction with drones.