Call for Papers

Topics

The workshop contains a broad spectrum of research topics encountered in dynamic environments, including but not limited to:

- Learning frameworks for developing robust and adaptable policies in ever-changing environments.
- Data augmentation techniques to increase the diversity and realism of training datasets for dynamic scenarios.
- Simulations to generate varied and complex dynamic environments for training and evaluation.
- Fast and reactive motion planning algorithms for real-time adaptation to environmental changes and disturbances.
- Techniques for smooth, agile, and safe robot motions under high-speed and unpredictable conditions.
- Task and behavior abstractions for scalable high-level planning in dynamic, multi-agent environments.
- Hierarchical policy architectures for combining high-level decision-making with reactive low-level control.
- Intention inference methods for anticipating human actions or coordinating with other robots in collaborative tasks.
- World models to forecast environmental changes and agent behaviors for proactive decision-making.
- Frameworks for integrating Large Language Models into robotic systems while preserving low-latency, reactive control.
- Reasoning methods to improve explainability, interpretability, and robustness in unforeseen scenarios.
- Benchmarks and standardized tasks for evaluating robustness, reactivity, and safety in dynamic environments.