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CalQNet - Detection of calibration quality for life-long stereo camera setups
(2021)2021 IEEE Intelligent Vehicles Symposium (IV)Many mobile robotic platforms rely on an accurate knowledge of the extrinsic calibration parameters, especially systems performing visual stereo matching. Although a number of accurate stereo camera calibration methods have been developed, which provide good initial 'factory' calibrations, the determined parameters can lose their validity over time as the sensors are exposed to environmental conditions and external effects. Thus, on ...Conference Paper -
SemSegMap – 3D Segment-based Semantic Localization
(2021)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)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 are equipped with high-accuracy 3D LiDAR sensors, which allow a geometric mapping, and cameras able to provide semantic cues of the environment. Segment-based mapping and localization have been applied with great success to 3D point-cloud data, while semantic ...Conference Paper -
Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning
(2022)2022 International Conference on Robotics and Automation (ICRA)Visual-inertial sensors have a wide range of applications in robotics. However, good performance often requires different sophisticated motion routines to accurately calibrate camera intrinsics and inter-sensor extrinsics. This work presents a novel formulation to learn a motion policy to be executed on a robot arm for automatic data collection for calibrating intrinsics and extrinsics jointly. Our approach models the calibration process ...Conference Paper