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