ICRA 2021 튜토리얼 / 워크샵 리스트

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Workshops / Tutorials

  • Digital Twins for Robots in Industrial Applications
  • Opportunities and Challenges with Autonomous Racing
    • 9:00 GMT-04
  • Perception and Action in Dynamic Environments
  • Robust Perception For Autonomous Field Robots in Challenging Environments
    • Davide Scaramuzza - Robust Perception For Cars And Drones
    • CJ Taylor - UPSLAM : Union of Panoramas SLAM
    • Sebastian Scherer - Robust Navigation with Visual and Thermal Sensors in Degraded Visual Environments
    • Jeanette Bohg - Detect, Reject, Correct: Cross-modal Compensation of Corrupted Sensors
    • Claire Tomlin - Learning-Based Waypoint Navigation: a Viewpoint on Perception, Planning, and Control
    • Larry Matthies - Terrain-relative navigation for guided descent on Titan
    • Sanjiv Singh - Perceptual robustness to obscurants and the world itself
    • Tim Barfoot - Dark, Damp, and Dynamic: Recent Progress on Robotic Localization in Challenging Environments
    • 9:00 GMT-04
  • Workshop on Visual-Inertial Navigation Systems
    • 9:00 GMT-04
  • Resilient and Long-Term Autonomy for Aerial Robotic Systems
    • 8:00 GMT-04

 

Papers

  • Optimization-Based Visual-Inertial SLAM Tightly Coupled with Raw GNSS Measurements
  • LiTAMIN2: Ultra Light LiDAR-Based SLAM Using Geometric Approximation Applied with KL-Divergence
  • Compositional and Scalable Object SLAM
  • Visual Place Recognition Via Local Affine Preserving Matching
  • Towards Real-Time Semantic RGB-D SLAM in Dynamic Environments
  • Voxelized GICP for Fast and Accurate 3D Point Cloud Registration
  • Markov Parallel Tracking and Mapping for Probabilistic SLAM
  • Avoiding Degeneracy for Monocular Visual SLAM with Point and Line Features
  • TT-SLAM: Dense Monocular SLAM for Planar Environments
  • OV2SLAM : A Fully Online and Versatile Visual SLAM for Real-Time Applications
  • DOT: Dynamic Object Tracking for Visual SLAM
  • DefSLAM: Tracking and Mapping of Deforming Scenes from Monocular Sequences (I)
  • An Equivariant Filter for Visual Inertial Odometry
  • Run Your Visual-Inertial Odometry on NVIDIA Jetson: Benchmark Tests on a Micro Aerial Vehicle
  • Simple but Effective Redundant Odometry for Autonomous Vehicles
  • Revisiting Visual-Inertial Structure-From-Motion for Odometry and SLAM Initialization
  • RigidFusion: Robot Localisation and Mapping in Environments with Large Dynamic Rigid Objects
  • Tight Integration of Feature-Based Relocalization in Monocular Direct Visual Odometry
  • Adaptive Robust Kernels for Non-Linear Least Squares Problems
  • A Front-End for Dense Monocular SLAM Using a Learned Outlier Mask Prior
  • HyperMap: Compressed 3D Map for Monocular Camera Registration
  • Robust Skin-Feature Tracking in Free-Hand Video from Smartphone or Robot-Held Camera, to Enable Clinical-Tool Localization and Guidance
  • VOLDOR-SLAM: For the Times When Feature-Based or Direct Methods Are Not Good Enough
  • ROBIN: A Graph-Theoretic Approach to Reject Outliers in Robust Estimation Using Invariants
  • Kimera-Multi: A System for Distributed Multi-Robot Metric-Semantic Simultaneous Localization and Mapping
  • Semantic SLAM with Autonomous Object-Level Data Association
  • Semantic and Geometric Modeling with Neural Message Passing in 3D Scene Graphs for Hierarchical Mechanical Search
  • Structure Reconstruction Using Ray-Point-Ray Features: Representation and Camera Pose Estimation
  • Lightweight 3-D Localization and Mapping for Solid-State LiDAR
  • BALM: Bundle Adjustment for Lidar Mapping
  • Tactile SLAM: Real-Time Inference of Shape and Pose from Planar Pushing
  • SD-DefSLAM: Semi-Direct Monocular SLAM for Deformable and Intracorporeal Scenes
  • Direct Sparse Mapping (I)
  • Simultaneous Multi-Level Descriptor Learning and Semantic Segmentation for Domain-Specific Relocalization
  • Pose Estimation for Vehicle-Mounted Cameras Via Horizontal and Vertical Planes
  • Lightweight Semantic Mesh Mapping for Autonomous Vehicles
  • A Complete, Accurate and Efficient Solution for the Perspective-N-Line Problem
  • Accelerating Robot Dynamics Gradients on a CPU, GPU, and FPGA
  • Robust Place Recognition Using an Imaging Lidar
  • A Switching-Coupled Backend for Simultaneous Localization and Dynamic Object Tracking
  • SLAAM: Simultaneous Localization and Additive Manufacturing (I)
  • Asynchronous Multi-View SLAM
  • LVI-SAM: Tightly-Coupled Lidar-Visual-Inertial Odometry Via Smoothing and Mapping
  • Distributed Client-Server Optimization for SLAM with Limited On-Device Resources
  • IMU Data Processing for Inertial Aided Navigation: A Recurrent Neural Network Based Approach
  • Robust Semantic Map Matching Algorithm Based on Probabilistic Registration Model
  • Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry
  • Greedy-Based Feature Selection for Efficient LiDAR SLAM
  • Road Mapping and Localization Using Sparse Semantic Visual Features
  • RoadMap: A Light-Weight Semantic Map for Visual Localization towards Autonomous Driving
  • Visual Semantic Localization Based on HD Map for Autonomous Vehicles in Urban Scenarios
  • Hybrid Bird’s-Eye Edge Based Semantic Visual SLAM for Automated Valet Parking
  • CamVox: A Low-Cost and Accurate Lidar-Assisted Visual SLAM System
  • PSF-LO: Parameterized Semantic Features Based Lidar Odometry
  • PicoVO: A Lightweight RGB-D Visual Odometry Targeting Resource-Constrained IoT Devices
  • CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth
  • Deep Online Correction for Monocular Visual Odometry
  • Robust Improvement in 3D Object Landmark Inference for Semantic Mapping
  • YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection
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