Recent advances in large-scale robot data have opened up possibilities for developing general-purpose
policies for tabletop manipulation, while progress in universal, cross-embodiment end-to-end navigation has
significantly advanced mobility. This convergence naturally motivates research into mobile
manipulation (MoMA), an
interdisciplinary field that integrates mobility with dexterity to enable robots to operate in large,
dynamic, and human-centric environments. Compared to tabletop setups, mobile manipulation presents distinct
challenges, including hardware design trade-offs (e.g., bimanual arms, torso structures, wheeled or legged
bases), low-level control complexities for whole-body coordination, and scalability challenges in real-world
data collection and skill learning. The field also raises fundamental questions about sim-to-real transfer,
egocentric vision, and long-horizon reasoning. Furthermore, mobile manipulators introduce new dimensions to
human-robot interaction, requiring safety and adaptability in extended workspaces. Addressing these
challenges will unlock the full potential of mobile manipulators across unstructured environments such as
homes, hospitality, logistics, gastronomy, retail, and agriculture, driving progress toward general-purpose,
intelligent robots. Key topics include:
Tasks and New Challenges: What are the critical tasks and application domains for mobile
manipulation that should be prioritized? What additional challenges does mobile manipulation present
compared to a tabletop setup?
Hardware Design: What is the optimal form factor for a mobile manipulator? Should we prioritize
anthropomorphic designs or appliance-like robots? Specifically, how should we decide between bimanual
arms, torso structures, wheeled bases, or legged systems?
Low-level Control: Controlling a robot with many DoFs is a significant challenge. How can we
effectively integrate planning and control for executing low-level motions and whole-body coordination?
Egocentric Perception and Scene Representation: What new challenges arise in mobile manipulation
with moving cameras? How does it impact the formulation of action space and visual representations in
the 3D scenes?
Real-world Data Scaling: Can advanced human-robot interfaces enhance teleoperation and motion
capture systems for demonstration collection? How can action-free videos facilitate skill learning in
the mobile manipulation domain?
Sim-to-Real Transfer: How can simulation accelerate learning for mobile manipulation while
ensuring effective real-world deployment? Can sim-to-real techniques developed for navigation be adapted
to mobile manipulation?
Long-horizon Planning and Reasoning: How can mobile manipulators efficiently plan and execute
long-horizon tasks that require multiple sequential interactions and reasoning? How can large
pre-trained models (e.g., LLM, VLM, VLA, World Models) facilitate new capabilities of mobile robots?
Human-Robot Interaction: Mobile manipulators work in the extended workspace. What new challenges
and opportunities does it pose and what safety considerations should be addressed in human-centric
environments?
By addressing these questions, the workshop aims to foster discussions on advancing next-generation
systems and learning for mobile manipulation.
Call for Papers
We are excited to announce the Call for Papers for the RSS MoMA workshop. We invite original contributions
presenting novel ideas, research, and applications relevant to the workshop’s theme.
Important Dates
Event
Date
Submission Deadline
May 25th 11:59PM UTC-0, 2025
Notification
June 1st, 2025
Camera-Ready
June 19th 11:59PM PT, 2025
Submission Guidelines
Page Limit: There are no page length requirements, but we suggest a length around 4-9
pages long. There is no limit on
the number of pages for references or appendices.
Formatting: Submissions are encouraged to use the RSS 2025, IROS 2025, CoRL 2025,
NeurIPS 2025 templates.
Anonymity: All submissions must be anonymized. Please remove any author names,
affiliations, or identifying information.
Relevant Work: We welcome references to recently published, relevant work (e.g., RSS,
CoRL, ICRA, and CVPR).
Archival Status: All accepted papers are non-archival. Submitting to multiple
non-archival workshops is permitted.
