Deformation Control

Deformation control focuses on precisely manipulating the shape of deformable objects, such as cloth or linear objects, using robotic systems. Current research emphasizes developing both model-based and model-free control strategies, employing techniques like Cosserat models, Jacobian matrices derived from vision feedback, and data-driven approaches such as neural networks to accurately predict and control deformation. These advancements are crucial for improving robotic manipulation in various applications, including tasks involving flexible materials in manufacturing, domestic settings, and even collaborative robotics with large-scale multi-agent systems. The development of robust and efficient control algorithms is key to enabling more sophisticated and versatile robotic interactions with deformable objects.