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The workshop aims to explore different aspects that will potentially allow robots to autonomously manipulate deformable objects in the near future. Enabling such manipulation is crucial for a variety of domains and tasks, e.g., domestic, industrial and surgical contexts, which involve various forms of object deformability. However, the complexity of representing and modeling the dynamics of these objects results in the lack of a current unified solution that can be adapted to a wide range of objects. Specifically, the workshop will focus on, but is not limited to, the following topics for deformable object manipulation:
- Representation and state estimation
- Simulation and modeling
- Transfer from simulation to reality
- Learning to manipulate using data-driven methods such as reinforcement learning and learning from demonstrations
- Perception: state tracking, parameter identification, property detection (e.g. landmarks for garments) and classification, etc.
- Control, visual servoing and planning
- Specialized tools, e.g. grippers, and sensors
- Multi-arm manipulation
- Application-specific challenges: cloth folding, surgical tasks, precision agriculture, etc.