The 4th Annual Conference on Robot Learning (CoRL 2020) is soliciting contributions at the intersection of robotics and machine learning. CoRL is a selective, single-track conference for robot learning research, covering a broad range of topics spanning robotics, ML and control, and including theory and applications.
Papers offering new advances in robot learning are invited. Topics include:
Imitation learning and (inverse) reinforcement learning
Probabilistic learning and representation of uncertainty in robotics
Model-free learning for decision-making
Machine learning for system identification and control
Bio-inspired learning and control
State estimation, localization and mapping
Multimodal perception, sensor fusion, and computer vision
Learning for human-robot interaction and natural language instruction processing
Applications of robot learning in manipulation, mobility, driving, flight, and other areas of robotics
Authors are strongly encouraged to demonstrate how their methods relate to robotics and applications. Authors are also strongly encouraged to submit their code as supplementary material to the paper.
Accepted papers will be published in the JMLR Workshop & Conference Proceedings series and presented either as posters, spotlights or long talks in the plenary session. This year reviews and rebuttals of accepted papers will be made publicly available.