What is This Workshop About?
The past decade has seen significant advancements in multi-robot systems, particularly in decision-making, coordination, control, navigation, and reinforcement learning for multi-agent systems. Despite this progress, the real-world deployment of robotic teams remains a challenge. This workshop aims to bring together experts from academia, industry, and government to explore key research areas and identify the critical barriers preventing scalable multi-robot deployment from both theoretical and practical perspectives.
Current research in multi-robot systems predominantly assumes cooperative or optimally performing agents, often overlooking scenarios where certain agents may act adversarially or perform suboptimally due to uncertainty or environmental disturbances. A critical challenge in advancing real-world deployment is the development of resilient decision-making algorithms that enable robotic teams to adapt to unforeseen situations, operate safely in dynamic environments, and achieve mission objectives despite uncertainty and potential adversarial influences. Additionally, the absence of datasets and benchmarks that account for adversarial factors in real-world multi-robot tasks remains a significant barrier, limiting the ability to rigorously evaluate and improve the robustness of autonomous systems in such conditions.
Addressing these challenges requires robust methodologies that integrate decision-making under uncertainty, adversarial resilience, and partial information handling, particularly in the context of dynamically evolving conditions.
To advance the field, the workshop will focus on recent theoretical and practical advancements, with particular emphasis on areas such as model-based reinforcement learning, multi-robot planning, and adaptive control strategies. Through invited talks, panel discussions, and interactive sessions, we will foster collaboration across disciplines to develop scalable, verifiable, and deployable solutions for real-world multi-robot systems.
The workshop will feature a lightning talks session and invites high-quality paper submissions on decision-making in multi-robot and multi-agent systems. Topics of interest include, but are not limited to:
- Multi-Robot planning, coordination, and cooperation
- Estimation, perception, and modeling for large-scale robot teams
- Robust and resilient control strategies
- Learning-based approaches for multi-agent systems
- Decision-making under uncertainty and adversarial influence
- Scalable Multi-agent reinforcement learning
- Real-world benchmarks and datasets for multi-robot systems
By bringing together leading researchers and practitioners, this workshop aims to shape the future of scalable and resilient multi-robot autonomy.
We are currently seeking submissions for posters and lightning talks. Consult the Call for Contributions page for more details on how to submit your work. A selection of accepted papers will be invited to present a lightning talk during the workshop, and a subset of these will also be considered for special honors (details to be announced).
Important Dates
| Date | Event |
|---|---|
| May 16, 2025 (AoE) | Paper Submission Deadline |
| June 1, 2025 | Notification of Acceptance |
| June 19, 2025 (AoE) | Camera-ready Paper Deadline |
| June 25, 2025 (8:40am–6:00pm) | Workshop Date |
