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Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes
(2019)arXivDeep learning has enabled remarkable advances in scene understanding, particularly in semantic segmentation tasks. Yet, current state of the art approaches are limited to a closed set of classes, and fail when facing novel elements, also known as out of distribution (OoD) data. This is a problem as autonomous agents will inevitably come across a wide range of objects, all of which cannot be included during training. We propose a novel ...Working Paper -
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Fusion of Optical Flow and Inertial Measurements for Robust Egomotion Estimation
(2014)In this paper we present a method for fusing optical flow and inertial measurements. To this end, we derive a novel visual error term which is better suited than the standard continuous epipolar constraint for extracting the information contained in the optical flow measurements. By means of an unscented Kalman filter (UKF), this information is then tightly coupled with inertial measurements in order to estimate the egomotion of the sensor ...Working Paper -
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Autonomous Electric Race Car Design
(2017)arXivAutonomous driving and electric vehicles are nowadays very active research and development areas. In this paper we present the conversion of a standard Kyburz eRod into an autonomous vehicle that can be operated in challenging environments such as Swiss mountain passes. The overall hardware and software architectures are described in detail with a special emphasis on the sensor requirements for autonomous vehicles operating in partially ...Working Paper -
Dynamic System Identification, and Control for a cost effective open-source VTOL MAV
(2017)arXivWorking Paper -
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A decentralized multi-agent unmanned aerial system to search, pick up, and relocate objects
(2017)arXivWorking Paper -
Build your own visual-inertial odometry aided cost-effective and open-source autonomous drone
(2017)arXivWorking Paper