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VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments
(2019)2019 IEEE Intelligent Vehicles Symposium (IV)Conference Paper -
Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Optimization-Based Terrain Analysis and Path Planning in Unstructured Environments
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Object Classification Based on Unsupervised Learned Multi-Modal Features For Overcoming Sensor Failures
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Redundant Perception and State Estimation for Reliable Autonomous Racing
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
From coarse to fine: Robust hierarchical localization at large scale
(2019)Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019)Conference Paper -
An Approach for Semantic Segmentation of Tree-like Vegetation
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Learning to Predict the Wind for Safe Aerial Vehicle Planning
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Fault-tolerant Flight Control of a VTOL Tailsitter UAV
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Predicting Unobserved Space For Planning via Depth Map Augmentation
(2019)2019 19th International Conference on Advanced Robotics (ICAR)Safe and efficient path planning is crucial for autonomous mobile robots. A prerequisite for path planning is to have a comprehensive understanding of the 3D structure of the robot's environment. On Micro Air Vehicles (MAVs) this is commonly achieved using low-cost sensors, such as stereo or RGB-D cameras. These sensors may fail to provide depth measurements in textureless or IR-absorbing areas and have limited effective range. In path ...Conference Paper