Robot learning researchers
Researchers working on learned policies, representation learning, data-efficient adaptation, foundation models, and sim-to-real transfer for physical interaction.
Intended Audience
Locomotion, manipulation, and control communities
Researchers studying whole-body control, legged or humanoid robots, mobile manipulators, non-prehensile skills, and contact-rich motion.
Benchmark and deployment researchers
Researchers designing tasks, datasets, simulation assets, evaluation protocols, safety metrics, and real-world testbeds for contact-rich loco-manipulation.
Early-career researchers
Late-stage PhD students, postdoctoral researchers, and others preparing for their next research role are especially welcome. Posters and discussions offer space to share work and meet prospective mentors, collaborators, and academic or industry research groups.
Workshop Outcomes
Accepted papers, slides, and the post-workshop open-problems report will be shared on this website.
Contact
For questions about participation, submissions, accessibility, or workshop logistics, contact the organizing team.