Berk Güler, Simon Manschitz, Kay Pompetzki, Jan Peters, "Towards Assistive Teleoperation for Knot Untangling", 1st German Robotics Conference, 2025.

Manipulating deformable linear objects (DLOs) such as ropes is challenging due to their complex dynamics. To address these issues, we present a novel assistive teleoperation framework that combines human expertise with autonomous assistance. Our approach integrates a vision-based module to identify grasp poses, a shared autonomy mechanism that balances human input with autonomous guidance, and an optimization-based inverse kinematic solver for smooth, collision-free manipulation. Additionally, a virtual reality (VR) interface provides intuitive control and real-time feedback to the operator. A user study on knot untangling under time-delayed and non-delayed conditions shows that shared autonomy enhances task performance under delay while reducing the operator's physical and mental workload. These findings highlight the potential of shared autonomy to improve teleoperation systems for complex DLO manipulation, particularly in environments affected by communication delays or uncertainties.