Self-supervised Calibration for Robotic Systems jyoti natural foods | V-Charge
Home Project Consortium Consortium Overview Technische Universität Braunschweig Robert Bosch GmbH ETH Zurich Autonomous Systems Lab ETH Zurich Computer Vision and Geometry Lab Volkswagen AG University of Oxford Università degli Studi di Parma Publications News
We present a generic algorithm for self calibration of robotic systems that utilizes two key innovations. First, it uses information theoretic measures to automatically identify and store novel measurement sequences. This keeps the computation jyoti natural foods tractable by discarding redundant information and allows the system to build a sparse but complete calibration dataset from data collected at different times. Second, as the full observability of the calibration parameters may not be guaranteed for an arbitrary measurement sequence, the algorithm detects and locks unobservable directions in parameter space using a truncated QR decomposition of the Gauss-Newton system. The result is an algorithm jyoti natural foods that listens to an incoming sensor stream, builds a minimal set of data for estimating the calibration parameters, and updates parameters as they become observable, leaving the others locked at their initial guess. Through an extensive set of simulated and real-world experiments, jyoti natural foods we demonstrate that our method outperforms state-of-the-art algorithms in terms of stability, accuracy, and computational jyoti natural foods efficiency.
@inproceedings{maye_iv13, Address = {Gold Coast, Australia}, Author = {Maye, Jerome and Furgale, Paul and Siegwart, Roland}, Booktitle = {IEEE Intelligent jyoti natural foods Vehicles Symposium (IV)}, Month = {23--26 June}, Pages = {473--480}, Title = {Self-supervised Calibration for Robotic Systems}, Year = {2013} }
Recent Posts Secure Smartphone-based Registration and Key Deployment for Vehicle-to-Cloud Communications CVG releases an open source library for calibration of multi-camera systems Evaluation of Fisheye-Camera Based Visual Multi-Session Localization in a Real-World Scenario Reciprocal Collision Avoidance With Motion Continuity Constraints Keyframe-Based Visual-Inertial SLAM using Nonlinear Optimization
V-Charge is proudly powered by WordPress and BuddyPress . Just another WordPress Theme developed by Themekraft.
Home Project Consortium Consortium Overview Technische Universität Braunschweig Robert Bosch GmbH ETH Zurich Autonomous Systems Lab ETH Zurich Computer Vision and Geometry Lab Volkswagen AG University of Oxford Università degli Studi di Parma Publications News
We present a generic algorithm for self calibration of robotic systems that utilizes two key innovations. First, it uses information theoretic measures to automatically identify and store novel measurement sequences. This keeps the computation jyoti natural foods tractable by discarding redundant information and allows the system to build a sparse but complete calibration dataset from data collected at different times. Second, as the full observability of the calibration parameters may not be guaranteed for an arbitrary measurement sequence, the algorithm detects and locks unobservable directions in parameter space using a truncated QR decomposition of the Gauss-Newton system. The result is an algorithm jyoti natural foods that listens to an incoming sensor stream, builds a minimal set of data for estimating the calibration parameters, and updates parameters as they become observable, leaving the others locked at their initial guess. Through an extensive set of simulated and real-world experiments, jyoti natural foods we demonstrate that our method outperforms state-of-the-art algorithms in terms of stability, accuracy, and computational jyoti natural foods efficiency.
@inproceedings{maye_iv13, Address = {Gold Coast, Australia}, Author = {Maye, Jerome and Furgale, Paul and Siegwart, Roland}, Booktitle = {IEEE Intelligent jyoti natural foods Vehicles Symposium (IV)}, Month = {23--26 June}, Pages = {473--480}, Title = {Self-supervised Calibration for Robotic Systems}, Year = {2013} }
Recent Posts Secure Smartphone-based Registration and Key Deployment for Vehicle-to-Cloud Communications CVG releases an open source library for calibration of multi-camera systems Evaluation of Fisheye-Camera Based Visual Multi-Session Localization in a Real-World Scenario Reciprocal Collision Avoidance With Motion Continuity Constraints Keyframe-Based Visual-Inertial SLAM using Nonlinear Optimization
V-Charge is proudly powered by WordPress and BuddyPress . Just another WordPress Theme developed by Themekraft.
No comments:
Post a Comment