This workshop is meant to be a platform of exchange between the three communities of computer vision, machine learning, and robotics. We want encourage them to find feasible solutions that bridge the gap between stand-alone perception and robotic related tasks such as motion or assembly planning, visual servoing and grasping. A main topic is how sensing, manipulation and planning can be combined to yield mutual benefits. We also search for scalable learning-based approaches that require little supervision and examine them on their benefits and limitations. This can include learning in simulation, transfer and few-shot learning, automatic labeling or reinforcement learning. Are end-to-end learning approaches really the right way to go or are modular pipelines still preferable due to better introspection? Are current subtask metrics suitable indicators for execution success? What is necessary to address the needs of end-user applications in terms of scalability, robustness, runtime, cost, maintainability and fail-safety?

Invited Speakers

Call for Papers

We solicit 2-4 page extended abstracts (following RSS style guidelines). The submissions can include: late-breaking results, under review material, or archived. We strongly encourage the preparation of live demos or videos accompanying the submission.

Submitted papers will be reviewed by the organizers and invited reviewers. Accepted contributions will be presented as posters or within the Demo/Video Talk format. Selected papers are further featured as spotlight talks. All accepted contributions and posters will be posted on the workshop website upon author approval.

Submission is now open on EasyChair SLIPP-2019RSS, please take note on the submission deadline.


Time Topic
8:00 - 9:00 On-site Registration
9:00 - 9:10 Introductory Remarks
9:10 - 9:50 Invited Talk: Maxim Likhachev
Offline Learning for Online Planning
9:50 - 10:30 Invited talk: Renaud Detry
Combining Semantic and Geometric Scene Understanding: From Robot Manipulation to Planetary Exploration
10:30 - 10:45 Poster Spotlights
10:45 - 11:30 Coffee Break + Posters
11:40 - 12:20 Invited Talk: Sergey Levine
Data-Driven Robotic Reinforcement Learning
12:20 - 1:00 Invited Talk: Leonel Rozo
Exploiting Geometric and Temporal Structure in Object-centric Skills Learning
1:00 - 1:45 Lunch Break
1:50 - 2:30 Invited Talk: Gilwoo Lee
Bayesian Reinforcement Learning
2:30 - 3:15 Coffee Break + Posters
3:20 - 4:00 Invited Talk: Dieter Fox
Simulation for Training Manipulation Systems
4:00 - 4:20 Demo/Video Talks
4:20 - 4:40 Discussion with participation of the audience and experts


June 7, 2019 (23:59 Pacific Time) Paper Submission Deadline
June 14, 2019 (23:59 Pacific Time) Paper Acceptance Notification
June 22, 2019 (Saturday) Workshop
WS1-2 Scalable Learning for Integrated Perception and Planning
Faculty of Engineering, Building 82, Room 00 006


Should you have any questions, please do not hesitate to contact the organizing committee at scalableroboticlearning@dlr.de: