254 citations · 509 across the 15 of their papers we have counts for
6 papers · 1 filter
Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning
Yunke Ao, Le Chen, Florian Tschopp +3
Visual-inertial sensors have a wide range of applications in robotics. However, good performance often requires different sophisticated motion routines to accurately calibrate came…
Superquadric Object Representation for Optimization-based Semantic SLAM
Florian Tschopp, Juan Nieto, Roland Siegwart +1
Introducing semantically meaningful objects to visual Simultaneous Localization And Mapping (SLAM) has the potential to improve both the accuracy and reliability of pose estimates,…
SemSegMap- 3D Segment-Based Semantic Localization
Andrei Cramariuc, Florian Tschopp, Nikhilesh Alatur +6
Localization is an essential task for mobile autonomous robotic systems that want to use pre-existing maps or create new ones in the context of SLAM. Today, many robotic platforms…
3D3L: Deep Learned 3D Keypoint Detection and Description for LiDARs
Dominic Streiff, Lukas Bernreiter, Florian Tschopp +2
With the advent of powerful, light-weight 3D LiDARs, they have become the hearth of many navigation and SLAM algorithms on various autonomous systems. Pointcloud registration metho…
CalQNet -- Detection of Calibration Quality for Life-Long Stereo Camera Setups
Jiapeng Zhong, Zheyu Ye, Andrei Cramariuc +4
Many mobile robotic platforms rely on an accurate knowledge of the extrinsic calibration parameters, especially systems performing visual stereo matching. Although a number of accu…
Hough2Map -- Iterative Event-based Hough Transform for High-Speed Railway Mapping
Florian Tschopp, Cornelius von Einem, Andrei Cramariuc +5
To cope with the growing demand for transportation on the railway system, accurate, robust, and high-frequency positioning is required to enable a safe and efficient utilization of…