  Manipulating deformable objects arises in daily life and numerous
applications. Despite phenomenal advances in industrial robotics, manipulation
of deformable objects remains mostly a manual task. This is because of the high
number of internal degrees of freedom and the complexity of predicting its
motion. In this paper, we apply the computationally efficient position-based
dynamics method to predict object motion and distance to obstacles. This
distance is incorporated in a control barrier function for the resolved motion
kinematic control for one or more robots to adjust their motion to avoid
colliding with the obstacles. The controller has been applied in simulations to
1D and 2D deformable objects with varying numbers of assistant agents,
demonstrating its versatility across different object types and multi-agent
systems. Results indicate the feasibility of real-time collision avoidance
through deformable object simulation, minimizing path tracking error while
maintaining a predefined minimum distance from obstacles and preventing
overstretching of the deformable object. The implementation is performed in
ROS, allowing ready portability to different applications.
