Manipulation Trajectory

Manipulation trajectory research focuses on enabling robots to perform complex tasks by generating and executing optimal movement sequences for interacting with objects. Current efforts concentrate on improving trajectory planning algorithms, including those leveraging contact-implicit optimization, transformer-based architectures for deformable objects, and diffusion models for collision avoidance in multi-arm systems. These advancements utilize techniques like neural object descriptors and tactile feedback to enhance robustness and generalizability across diverse tasks and environments, ultimately aiming to improve robotic dexterity and efficiency in real-world applications.