Environment generation is a growing research topic with a rapidly increasing number of applications in robotics. We identify three lines of research in environment generation which, while focusing on different goals, draw upon similar insights and often use related solution techniques: (1) Finding diverse scenarios to test and evaluate robotic systems. (2) Creating large-scale offline datasets of diverse robotics tasks and environments. (3) Open-ended co-evolution of robots and environments to form interactive curricula, which eventually leads to generalizable robots.
While each track has a different focus and success criteria, they also share common techniques to generate environments, e.g., using generative models trained with human-authored data, integrating robot performance outcomes in the generation process, and using predictive models of robot behaviors for efficient evaluation. The objectives of this workshop are to bring together researchers in the fields of scenario generation, open-ended co-evolution, procedural content generation, and generative modeling to raise awareness about overlapping solution techniques and identify the key challenges in generating environments that enhance the robustness and capabilities of deployed robotic systems. The workshop will include renowned experts from different fields as invited speakers, presentations from researchers submitting papers of original research, focus groups, poster sessions, and a panel session where the invited speakers will present their unique perspectives about the role that environment generation can play in robot science and systems.
This workshop will include keynote talks, contributed papers, and discussions to encourage interactions between researchers working in different sub-fields of environment generation. Our final schedule includes:
Talks from invited keynote speakers.
Contributed paper talks: 8 minute talks from the authors of each accepted paper.
Q&A session with invited panelists.
Submission open: May 1, 2023 (see the call for papers for submission instructions)
Submission deadline: May 17, 2023 May 25, 2023 (23:59 UTC-12)
Acceptance notification: June 10, 2023
Workshop: July 10, 2023
Aleksandra Faust, Research Scientist, Google Brain
Deepak Pathak, Assistant Professor, Carnegie Mellon University
Jeff Clune, Associate Professor, University of British Columbia
Mark Riedl, Professor, Georgia Institute of Technology
Matt Deitke, AI Researcher, Allen Institute for AI/University of Washington
Tim Rocktäschel, Research Scientist, DeepMind
(all times are in Korean Standard Time, UTC+9)
09:00 - 09:30: Introduction
09:30 - 10:00: Talk by Mark Riedl
10:00 - 10:30: Talk by Matt Deitke
10:30 - 11:00: Coffee Break
11:00 - 11:30: Talk by Jeff Clune
11:30 - 12:00: Talk by Aleksandra Faust
12:00 - 13:30: Lunch
13:30 - 14:00: Talk by Deepak Pathak
14:00 - 15:00: Panel (Add questions at https://pigeonhole.at/MAJC4E)
15:00 - 15:30: Coffee Break
15:30 - 16:00: Talk by Tim Rocktäschel
16:00 - 17:10: Paper Lightning Talks:
16:00 - 16:10: Li and Varakantham, Generalizable Policy through Diversity: Improving Unsupervised Environment Design
16:10 - 16:20: Zhang and Yang, Generating a Terrain-Robustness Benchmark for Legged Locomotion: A Prototype via Terrain Authoring and Active Learning
16:20 - 16:30: Tio and Varakantham, Zone of Proximal Development with Difficulty-Conditioned Generators
16:30 - 16:40: Ding et al., Semantically Adversarial Scene Generation with Explicit Knowledge Guidance
16:40 - 16:50: Lu et al., Synthetic Experience Replay
16:50 - 17:00: Bhatt et al., Surrogate Assisted Generation of Human-Robot Interaction Scenarios
17:00 - 17:10: Zhang et al., Multi-Robot Coordination and Layout Design for Automated Warehousing
Jack Parker-Holder, Research Scientist, DeepMind, jparkerholder<at>deepmind.com
Kuan Fang, Post-doctoral Scholar, University of California Berkeley, kuanfang<at>berkeley.edu
Minqi Jiang, PhD Student, University College London/Meta AI, msj<at>meta.com
Stefanos Nikolaidis, Assistant Professor, University of Southern California, nikolaid<at>usc.edu
Matthew Fontaine, PhD Student, University of Southern California, mfontain<at>usc.edu
Yachuan Hsu, PhD Student, University of Southern California, yachuanh<at>usc.edu
Varun Bhatt, PhD Student, University of Southern California, vsbhatt<at>usc.edu