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ICRA 2020 Notes

ICRA 2020 Notes

Top 5 papers so far

  • Realistic extrapolation of visual driving scenes in a simulator
  • ρ(r(yᵢ, x)) Graduated non-convexity. Change ρ slowly from convex function to a robust non-convex function.
  • Probabilistic Data Association via Mixture Models forRobust Semantic SLAM Kevin J. Doherty1, David P. Baxter1;�, Edward Schneeweiss1;2;�, and John J. Leonard (CSAIL) https://ras.papercept.net/proceedings/ICRA20/1656.pdf https://ras.papercept.net/proceedings/ICRA20/1656.mp4

    • Multiple hypothesis data association
    • Marginalizing out all possible hypothesis
    • Akin to max-mixtures Olson and Agarwal 2013
    • Add a binary data-association variable and the factor depends on the data-association variable.
    • GTSAM based optimization
    • Real time performance

Other papers

  • Visual localization with Google Earth images for robust global pose estimation of UAVs B. Patel, T. D. Barfoot, and A. P. Schoellig in Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2020. Accepted.

  • Metrically-Scaled Monocular SLAM Using Learned Scale Factors https://ras.papercept.net/proceedings/ICRA20/0017.pdf Greene, William Nicholas Massachusetts Institute of Technology Roy, Nicholas

    • combine depth prediction with metric unscaled slam Godard etal. [19],
    • Disparity estimator and predict D_l and D_r that map from I_l and I_r
    • Self supervised disparity estimator
    • With pyramids
    • Factor graph build from visual-inertial odometry
  • Inertial-Only Optimization for Visual-Inertial Initialization https://ras.papercept.net/proceedings/ICRA20/0447.pdf

    • Focuses on initialization for VIO. (a) Vision only (b) Inertial only (c) Visual inertial.
  • The empirical duality gap of constrained statistical learning https://arxiv.org/abs/2002.05183

    • Establishes the gap between parameteric approximation
  • Hierarchical Quadtree Feature Optical Flow Tracking Based Sparse Pose-Graph Visual-Inertial SLAM https://ras.papercept.net/proceedings/ICRA20/0584.pdf

    • Focuses on optical flow feature tracking for VIO
    • by using hierarchical quadtree based searching of matching image patches.
  • Robust 6D Object Pose Estimation by Learning RGB-D Features Meng Tian1, Liang Pan1, Marcelo H Ang Jr1and Gim Hee Lee2 https://ras.papercept.net/proceedings/ICRA20/0915.pdf

Autonomous driving papers

Add constraints to the lane detection for continuity and against loops.

Award papers

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