LEARNER

SLAM and Path Planning Middleware Package for Robots in Challenging Environments

LEARNER PUBLICATIONS

  • Increasing Illumination Invariance of Learning-Based Local Features Using Photo-Realistic Simulated Environments
    Submitted at the Robotics and Autonomous Systems, Elsevier
    SSRN open-access version: download.
  • A Deep Actor-Critic Reinforcement Learning Framework for Persistent Keypoint Detection under Challenging vSLAM Conditions
    Submitted at the Robotics and Automation Letters, IEEE
    Pre-print version: download
  • Low-Light Adaptation for Action Recognition-Enabled Robot Navigation
    Submitted at the Robotics, MDPI
    Pre-print version: download
  • MESA: A Multi-Environment Synthetic Adaptation Dataset for visual SLAM Evaluation and Feature Learning
    Presented in Proceedings of the European Conference on Mobile Robots, 2025
    Pre-print version: download
  • LEARNER: A SLAM and Path Planning Middleware Package for Dynamic and Visually Challenging Environments
    Submitted at the Cyber-Systems and Robotics, IET
    Pre-print version: download