Mastering Contact-rich Tasks by Combining Soft and Rigid Robotics with
Imitation Learning
Mastering Contact-rich Tasks by Combining Soft and Rigid Robotics with
Imitation Learning
Soft robots have the potential to revolutionize the use of robotic systems with their capability of establishing safe, robust, and adaptable interactions with their environment, but their precise control remains challenging. In contrast, traditional rigid robots offer high accuracy and repeatability but lack the flexibility of soft robots. We argue …