Agility, characterized by swift, precise, and adaptive movement in complex environments, is crucial for robots to fully exploit their capabilities. An agile robot can leap over obstacles, manipulate objects out of reach, navigate through tight spaces, and quickly adapt to unexpected changes. Historically, research in agile robotics has often been segmented. Whether it's a focus on specific platforms like arms, legs, or drones; a preference for classical control versus machine learning methods; or a distinct emphasis on either perception or low-level control, there's been a tendency to dive deep into individual areas. However, achieving true robotic agility demands an integrated approach that bridges these traditional divides. This workshop seeks to foster discussions that view agility as a comprehensive objective, necessitating collaboration across domains and platforms. The scope of the workshop thus focuses primarily on (but is not limited to) the following topics:
- System Design
- Hardware and mechanical considerations specific to agile robots.
- Unified agility through the integration of traditionally distinct robotic domains, such as whole-body mobile manipulation.
- Synchronization of grasp planning, motion planning, and time parameterization.
- Techniques and Challenges
- Integrating recent machine learning techniques, such as large language models, foundational models, and transformers, into agile robotics.
- Role of perception in enhancing robot agility.
- Stability, safety, and evaluation of robots operating at high speeds.
- Showcasing agility in real-world scenarios: fast bin-picking, quick assembly, speedy delivery robots, accurate object tossing and catching, and more.