Call for Papers: 1st Annual Conference on Robot Learning
The 1st Annual Conference on Robot Learning (CoRL 2017) is soliciting contribution at the intersection of robotics and machine learning. CoRL will be established as a selective, top-tier venue for robot learning research, covering a broad range of topics spanning robotics and ML, including both theory and practice:

Reinforcement learning
Model learning and control
State estimation, mapping, and computer vision
Multimodal perception and sensor fusion
Learning-based human robot interaction, natural language instruction processing
Applications in manipulation, mobility, driving, flight, and other areas of robotics
Bio-inspired learning and control

Robotics, autonomous perception, and control are undergoing a machine learning revolution. Now is the time to dedicate a venue that will combine fundamental advances in machine learning with an empirical exploration of robotics applications and theory. CoRL will be organized as a focused three-day meeting, with invited keynote talks and contributor presentations.

Additional information will be made available on the conference website: http://robot-learning.org

Location:
Mountain View, California, USA

Key dates:
Paper submission deadline: June 28, 2017 (both archival and workshop track)
Paper acceptance notification: September 1, 2017
Conference dates: November 13-15, 2017

General Chairs:
Vincent Vanhoucke, Google
Sergey Levine, UC Berkeley
Ken Goldberg, UC Berkeley

Publicity and Sponsorship Chair:
Debadeepta Dey, Microsoft Research

Area Chairs:
Abhinav Gupta, CMU
George Konidaris, Brown
Ingmar Posner, Oxford
Jianxiong Xiao, Princeton/AutoX
Leslie P. Kaelbling, MIT
Marc Deisenroth, UCL
Marc Pollefeys, Microsoft/ETH Zurich
Raia Hadsell, DeepMind